社会网络分析在国外旅游研究中的应用进展
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摘要
近年来社会网络分析在旅游相关研究中表现出超强的适应性,成为国内外旅游研究的流行范式之一。论文从研究视角和方法、研究内容以及中层理论的应用3个方面分析了国际旅游研究的十大权威期刊2009—2018年发表的社会网络分析相关文献67篇。在全面、系统、深入地梳理与分析的基础上,与10 a前相关文献综述进行对比,总结出近10 a社会网络分析在国外旅游研究中最新的进展。研究发现:①近10 a相关成果的研究视角进一步完善,表现为自我中心社会网视角以及与整体网结合的双重视角的研究成果显著增加;②研究方法多样化,关系数据的来源更加丰富,融合相关性分析等各类统计分析技术的定量研究成为主流,扎根理论等定性研究方法也开始应用;③研究对象从传统的目的地合作网、政策网等扩展至居民关系网、超链接网、口碑分享网、旅游形象网等;④研究内容从旅游社会关系网络结构的描述与分析转向关系网络的影响因素和效应分析,社会关系网络的形成、发展以及演化研究等;⑤社会网络分析相关中层理论的应用也有所拓展,其中社会资本理论对旅游相关议题的解释力进一步凸显,这体现了社会网络分析在旅游研究中的应用由变量测度到测度解释的转向。最后,文章总结了社会网络分析在国外旅游研究中应用存在的问题与难点,并展望了未来相关研究的方向。研究成果有助于全面把握旅游社会网络分析的最新研究动态与趋势,为进一步拓展和深化社会网络分析在旅游研究中的应用奠定基础。
In recent years, social network analysis(SNA) has been widely adopted in tourism research to become one of the most popular tourism research paradigms in China and internationally. This study analyzed 67 articles on SNA published in the top 10 authoritative international journals of tourism research from 2009 to 2018.Concepts of interest included SNA research perspectives and methods, research contents, and application of relevant theories. On the basis of a comprehensive, systematic analysis, the results of this study were compared with those of a literature review from 10 years ago. Findings provided an overview of international research progress in SNA in tourism within the past decade and revealed several trends. First, research perspectives have improved during the past 10 years, as evidenced by a remarkable increase in research results from an egocentric network perspective and its integration with the whole-network perspective. Second, research methods have diversified; sources of relational data have become richer, various statistical analysis techniques(e.g., correlation analysis) have been applied, and research using these quantitative techniques has entered the mainstream. Some researchers have also begun to use qualitative research methods, such as grounded theory. Third, research objects have expanded from destination cooperative networks and policy networks to residents' relational networks,hyperlink networks, electronic word-of-mouth networks, and tourism image networks. Fourth, the research focus has shifted from describing and analyzing network structures to examining influencing factors and effects along with the formation, development, and change of networks. Finally, application of relevant SNA theories has expanded; studies using the theory of social capital appear relatively rich, and the strong explanatory power of this theory on tourism-related issues has been revealed. These results reflect a shift in tourism SNA research from measuring variables to interpreting and explaining them. In this paper, we summarized the challenges associated with applying SNA in tourism research internationally and provided recommendations for future SNA research in China. This study contextualized the latest research trends in applying SNA to tourism studies and laid a foundation for subsequent work.
In recent years, social network analysis(SNA) has been widely adopted in tourism research to become one of the most popular tourism research paradigms in China and internationally. This study analyzed 67 articles on SNA published in the top 10 authoritative international journals of tourism research from 2009 to 2018.Concepts of interest included SNA research perspectives and methods, research contents, and application of relevant theories. On the basis of a comprehensive, systematic analysis, the results of this study were compared with those of a literature review from 10 years ago. Findings provided an overview of international research progress in SNA in tourism within the past decade and revealed several trends. First, research perspectives have improved during the past 10 years, as evidenced by a remarkable increase in research results from an egocentric network perspective and its integration with the whole-network perspective. Second, research methods have diversified; sources of relational data have become richer, various statistical analysis techniques(e.g., correlation analysis) have been applied, and research using these quantitative techniques has entered the mainstream. Some researchers have also begun to use qualitative research methods, such as grounded theory. Third, research objects have expanded from destination cooperative networks and policy networks to residents' relational networks,hyperlink networks, electronic word-of-mouth networks, and tourism image networks. Fourth, the research focus has shifted from describing and analyzing network structures to examining influencing factors and effects along with the formation, development, and change of networks. Finally, application of relevant SNA theories has expanded; studies using the theory of social capital appear relatively rich, and the strong explanatory power of this theory on tourism-related issues has been revealed. These results reflect a shift in tourism SNA research from measuring variables to interpreting and explaining them. In this paper, we summarized the challenges associated with applying SNA in tourism research internationally and provided recommendations for future SNA research in China. This study contextualized the latest research trends in applying SNA to tourism studies and laid a foundation for subsequent work.
引文
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赵政原,刘志高.2019.演化经济地理学视角下旅游目的地研究述评及启示[J].地理科学进展,38(1):101-110.[Zhao Z Y,Liu Z G.2019.Review of tourist destination research in the perspective of evolutionary economic geography.Progress in Geography,38(1):101-110.]
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Aarstad J,Ness H,Haugland S A,et al.2018.Imitation strategies and interfirm networks in the tourism industry:Astructure-agency approach[J].Journal of Destination Marketing&Management,9:166-174.
Albrecht J N.2013.Networking for sustainable tourism:Towards a research agenda[J].Journal of Sustainable Tourism,21(5):639-657.
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Asero V,Gozzo S,Tomaselli V.2016.Building tourism networks through tourist mobility[J].Journal of Travel Research,55(6):751-763.
Aubke F,W?ber K,Scott N,et al.2014.Knowledge sharing in revenue management teams:Antecedents and consequences of group cohesion[J].International Journal of Hospitality Management,41:149-157.
Baggio R,Scott N,Cooper C.2010.Network science:A review focused on tourism[J].Annals of Tourism Research,37(3):802-827.
Ben-David J.1964.Scientific growth:A sociological view[J].Minerva,2(4):455-476.
Benckendorff P,Zehrer A.2013.A network analysis of tourism research[J].Annals of Tourism Research,43:121-149.
Beritelli P.2011.Cooperation among prominent actors in a tourist destination[J].Annals of Tourism Research,38(2):607-629.
Burt R S.1992.Structural holes:The social structure of competition[M].Cambridge,MA:Harvard University Press.
Casanueva C,Gallegoá,García-Sánchez M-R.2016.Social network analysis in tourism[J].Current Issues in Tourism,19(12):1190-1209.
Chung J Y.2017.Online friendships in a hospitality exchange network:A sharing economy perspective[J].International Journal of Contemporary Hospitality Management,29(12):3177-3190.
Denicolai S,Cioccarelli G,Zucchella A.2010.Resourcebased local development and networked core-competencies for tourism excellence[J].Tourism Management,31(2):260-266.
Dredge D.2006.Policy networks and the local organisation of tourism[J].Tourism Management,27(2):269-280.
Erku?-?ztürk H,Erayd?n A.2010.Environmental governance for sustainable tourism development:Collaborative networks and organisation building in the Antalya tourism region[J].Tourism Management,31(1):113-124.
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