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題名：醫療旅遊與電子旅遊文獻的知識擴散軌跡：主路徑分析法
作者：李雅琪
作者(外文)：Yachi Lee
校院名稱：元智大學
系所名稱：管理學院博士班
指導教授：曾芳美
盧煜煬
學位類別：博士
出版日期：2017
主題關鍵詞：主路徑分析；集群分析；醫療旅遊；化妝品旅遊；移植旅遊；醫學美容；電子旅遊；社群媒體；main path analysis；clustering analysis；medical tourism；cosmetic tourism；transplant tourism；cosmetic surgery；eTourism；social media
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數位科技的快速進步加上全球自由經濟的興起，對於觀光、旅遊與旅館產業造成了很大的衝擊，隨之產生的大量相關文獻更造就了有效益的發展。針對旅遊業相關文獻進行系統化分析，對學術的知識創新與產業的知識管理有直接的貢獻。儘管許多學者嘗試識別與解析醫療旅遊(medical tourism)和電子旅遊(eTourism)相關的本質與議題，但其研究主體均相當多元與片斷。與醫療旅遊和電子旅遊相關的回顧性文獻大部分屬於定性研究，有些在檢視期刊論文的數量受到局限，有些則在研究領域受到限制。因此，本研究為填補這研究缺口，試圖以系統化、定量的方法來進行研究。
本研究採用以引文為基礎的定量分析方法：主路徑分析法(main path analysis)，來分析特定領域的研究發展軌跡、重要研究主題和近期熱門的研究議題，據此掌握學術研究的發展脈絡；並應用廣泛使用於分割社群網路結構之Girvan-Newman演算法進行集群分析(clustering analysis)。
透過觀光旅遊、旅館服務與醫療旅遊等文獻的闡釋，針對醫療旅遊與電子旅遊兩研究主題之學術論文發展軌跡進行探討。主要是利用主路徑分析法研究醫療旅遊和電子旅遊的發展趨勢，並發掘該領域重要文獻及其貢獻。電子旅遊是複雜且異質性高的領域，涉及不同類型的供應商、消費者與產品類型，故藉由集群分析以更精準地闡述電子旅遊研究的重要子題。
在醫療旅遊的研究中發現，文獻有兩條主要發展路徑：一條路徑(2004年至2013年)較偏重於醫療旅遊業的全球化歷程演變、動機因素、行銷策略與經濟分析；另一條路徑(2005年至2013年)則強調器官移植及相關議題。這兩條路徑最終合併到網絡中的一個名為醫學美容的共同節點，預示著未來研究將由器官移植到醫學美容的發展趨勢。
在電子旅遊的研究中(1988年至2013年)，文獻透過引文網絡找到連貫性結構，進而分成六子題。研究發現：「旅遊網站」和「旅遊部落格與社群媒體」二個子題的論文數量正加速成長，此暗示著供需雙方的資訊和談判力量的不對稱現象，從過去以供應商為中心已轉移到以消費者為中心的轉變，也闡釋了旅遊市場的去中介化趨勢和旅遊景點的分配已呈現長尾效應。
本研究提供一種獨特的文獻回顧方法，透過主路徑分析與集群分析可清楚掌握醫療旅遊與電子旅遊文獻的知識擴散軌跡、重要研究主題與未來研究發展趨勢，此研究方法亦可應用於其他領域的學術或專利文獻。
關鍵詞：主路徑分析、集群分析、醫療旅遊、化妝品旅遊、移植旅遊、醫學美容、電子旅遊、社群媒體
The advent of new digital technologies compounded with globalization and privatization have generated tremendous impact to the tourism, travel and hospitality industries. Despite the numerous scholarly attempts to identify and elaborate upon the nature and the associated issues related to the medical tourism and eTourism industries, this body of research could be described as heterogeneous and fragmented. Therefore, how to fill the gap by using a systematical approach that simultaneously captures the associations among the key issues and concerns proves to be important.
The main path analysis and a clustering method are used for this study. The main path analysis forms a unique quantitative and citation-based methodology to analyze the significant development trajectories, major research themes, and recent active research areas. The Girvan-Newman clustering algorithm is used to detect the community structure in networks.
The main path analysis is used to investigate the development trend of the synergistic relationship between both medical tourism and eTourism applications versus the new technologies. A more detailed clustering analysis is also performed for the discovery of major subtopics in eTourism due to its complexity and heterogeneity.
In the case of medical tourism, there are two distinctive development paths in the literature are found: one path (2004-2013) focuses more on the evolution of medical tourism, the motivation factors, marketing strategies, and economic analysis; the other path (2005-2013) emphasizes organ transplant and related issues. These two paths eventually merge to a common node in the citation network, which foretells transplantation to beautification as the future trend of research direction.
In the case of eTourism, the literature (1988-2013) is classified into six groups through discovering the coherence structure in a citation network. The analyses show that research on websites, blogs and social media on tourism is experiencing accelerated growth, which hints that there is a pendulum shift whereby the information and negotiation power asymmetry between the supply and demand sides are moving from provider-centric to consumer-centric. The associated market disintermediation phenomenon and long tail effects on the distribution of destinations are also elucidated.
This study presents a unique approach involving main path analysis and clustering analysis for the investigation of the knowledge diffusion of medical tourism and eTourism literature. Which enlightens better understanding of the research evolution with major research themes, key contributions and future trends. The main path analysis is not only appropriate for the study of medical tourism and eTourism, but also applicable for many other research fields of academic or patent literature.
Keywords: main path analysis, clustering analysis, medical tourism, cosmetic tourism, transplant tourism, cosmetic surgery, eTourism, social media.
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