社会网络分析在国外旅游研究中的应用进展

doi:10.18306/dlkxjz.2019.04.005

摘要/Abstract

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。

关键词: 社会网络分析, 旅游研究, 整体网, 自我中心社会网, 关系网络

Abstract:

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.

Key words: social network analysis, tourism research, the whole network, egocentric network, relationship networks

张红霞, 苏勤, 张影莎. 社会网络分析在国外旅游研究中的应用进展[J]. 地理科学进展, 2019, 38(4): 520-532.

Hongxia ZHANG, Qin SU, Yingsha ZHANG. Progress in the application of social network analysis in international tourism research[J]. PROGRESS IN GEOGRAPHY, 2019, 38(4): 520-532.

图/表 5

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表2

2009—2018年旅游社会网络分析的研究内容与进展概况"

研究议题		研究内容	研究进展
旅游目的地网络	从供给出发	目的地各类合作网络(Beritelli, 2011; Schaffer et al, 2012; Hwang et al, 2013; Kimbu et al, 2013; Lee et al, 2013; Ying et al, 2015; Luo et al, 2016; Kang et al, 2018) 线上网络(Luo et al, 2015; Ying et al, 2016; Raisi et al, 2018) 关系网络的演化(Ye et al, 2013; Pavlovich, 2014; Kim et al, 2018) 网络结构的影响(Denicolai et al, 2010; Erku?-?ztürk et al, 2010; Romeiro et al, 2010; Hwang et al, 2013; Ness et al, 2014; Ying et al, 2015; Luo et al, 2016; Hwang et al, 2017; Aarstad et al, 2018; Pulido-Fernández et al, 2018) 网络结构的影响因素(Strobl et al, 2013; Aubke et al, 2014; Ying et al, 2017; Kelliher et al, 2018)	各类细分网络、线上网络、不同网络之间的相互作用以及网络演化等议题受到关注;单纯以探讨网络结构为目的的成果减少,由网络结构的描述分析转向探讨网络结构的影响,即网络的效应分析;以网络和关系为切入点进行旅游目的地发展的相关问题探讨
	从供给出发	行动者的网络位置对信息扩散与分享(Ness et al, 2014)、创新意识(Zach et al, 2017)、资源获取能力和声望(Ford et al, 2012)、社区参与(Hwang et al, 2013)等的影响	将网络位置指标作为分析变量,分析行动者位置的影响
	从需求出发	区域吸引物网络的结构 (Stienmetz et al, 2015; Asero et al, 2016; Liu et al, 2017; Kang et al, 2018)和演化(Lee et al, 2018) 关系网络形成的潜在机制(Liu et al, 2017) 旅游目的地形象网络结构(Tasci et al, 2018; Wang et al, 2018)	由基于宏观旅游流转向基于微观旅游者移动角度的目的地网络研究;关注网络结构演化和旅游形象要素网
旅游学术研究网络		合著网的结构(Racherla et al, 2010; Ye et al, 2013)及演化(Nunkoo et al, 2013; Fan et al, 2017; K?seoglu et al, 2018) 共引、共被引网络(Benckendorff et al, 2013; García-Lillo et al, 2016; García-Lillo et al, 2018) 研究主题的网络特征(Nunkoo et al, 2013)及演化(Ying et al, 2011)	研究更加细致和深入,开始关注旅游分支领域的合作研究和知识结构、具体的研究内容和研究主题等议题;开展横向跨学科对比研究和纵向演化研究;社会网络的分析软件和技术应用较为深入
旅游相关人群的关系网络		居民(Hwang et al, 2013; Hwang et al, 2017)、旅游从业移民(Janta et al, 2012)的社会关系网络游客的线上网络(Luo et al, 2015) 主客双方的线上网络(Chung, 2017)	涉及旅游业务双方相关人群的关系网络和线上网络;研究方法多样化,如民族志、扎根理论、回归分析等的应用;成果还较为零散和有限

表2

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研究视角	定量	定性	两者结合	具体分析方法	数据来源
整体网	33	5	2	相关性分析、聚类分析、回归分析、结构方程模型、网络计量技术、文本分析、时间指数随机图模型、GIS等	问卷调查(实地、在线)、深度访谈、二手数据收集(报纸新闻、普查数据、网络数据抓取)
自我中心网	2	3	2	民族志、扎根理论、内容分析、相关性分析、回归分析	访谈、非参与式观察、问卷调查(实地、在线)、二手数据收集(统计数据、档案等)
双重视角	5	2	1	网络、民族志、回归分析等	访谈、焦点小组采访、在线问卷调查、二手数据收集(文献数据库)
内容	研究时段		研究特征
研究视角与研究方法新进展	2009年以前(王素洁等, 2009)		以整体网为主,自我中心社会网为辅;以定性研究为主,定量研究显著不足;多为零散的案例研究,理论提升少
研究视角与研究方法新进展	2009—2018年		自我中心社会网视角以及双重视角下的相关研究有所增多,探讨目的地居民关系、电子口碑关系网络等;定量分析显著增加,并逐渐成为主流,将网络指标作为变量,进而分析相关指标与旅游发展各类问题的关系;数据来源更加丰富,网络数据抓取等开始应用,研究方法多元化;理论总结与提升仍然缺失