中国情境下旅游用户生成内容研究综述及展望

doi:10.12054/lydk.bisu.163

旅游导刊 ›› 2021, Vol. 5 ›› Issue (4): 16-36.DOI: 10.12054/lydk.bisu.163

中国情境下旅游用户生成内容研究综述及展望

叶强¹,梁赛²,赵大营³

1.哈尔滨工业大学管理学院黑龙江哈尔滨 150001
2.南开大学旅游与服务学院天津 300350
3.岭南师范学院商学院广东湛江 524048

收稿日期:2020-04-24 修回日期:2021-06-17 出版日期:2021-08-30 发布日期:2021-08-27
作者简介:叶强（1972— ）,男,黑龙江哈尔滨人,哈尔滨工业大学管理学院教授,博士生导师,研究方向：电子旅游、用户生成内容、互联网金融等。|赵大营（1980— ）,男,黑龙江哈尔滨人,岭南师范学院商学院讲师,研究方向：电子旅游、用户在线行为、企业营销策略等。
基金资助:
国家重点研发计划(2017YFC1601903);国家自然科学基金项目“双向评论机制下社会压力对民宿共享平台用户在线行为的影响”(72002107);南开大学文科发展基金项目“双主体视角下基于异构信息源的民宿共享平台用户信息分享激励机制研究”(ZB21BZ0318);教育部人文社科基金项目“互惠理论视角下旅游民宿共享平台反馈策略研究”(20YJC630075);博士后科学基金面上项目“旅游民宿共享平台用户在线行为的影响因素研究”(2020M68087)

A Literature Review of Tourism User-Generated Content in the Context of China

YE Qiang¹,LIANG Sai²,ZHAO Daying³

1. School of Management, Harbin Institute of Technology, Harbin 150001, China
2. College of Tourism and Service Management, Nankai University, Tianjin 300350, China
3. Business School, Lingnan Normal University, Zhanjiang 524048, China

Received:2020-04-24 Revised:2021-06-17 Online:2021-08-30 Published:2021-08-27

摘要/Abstract

摘要：

本文基于对酒店业及旅游管理领域社会科学引文索引（SSCI）期刊中关于中国情境下旅游用户生成内容的文献计量分析,综述了中国情境下旅游用户生成内容的研究趋势,并展望了该领域未来研究方向。研究显示：香港理工大学、哈尔滨工业大学、中山大学和南开大学等高校在该研究领域做出了较大的学术贡献;在线旅游社区TripAdvisor中的在线评论是这类研究最常用的数据来源,且北京、香港、上海、广州等旅游热门城市是学者们关注的重点区域;在研究主题上,该领域的研究可分为用户生成内容的目的地形象感知研究、用户生成内容对旅游企业绩效的影响、用户生成内容的在线声誉管理及用户在线分享行为的激励机制4个方面。未来研究中,学者们可通过挖掘国内游客用户生成内容、探索国内旅游企业管理反馈策略及探讨国内民宿共享平台用户交互模式等方向,进一步深化和完善中国情境下旅游用户生成内容这一领域的研究。

关键词: 旅游用户生成内容; 中国情境; 研究进展; 综述

Abstract:

This paper reviews the research trend of tourism user-generated content in the Chinese context via bibliometric analysis of content in SSCI-indexed journals concerning the hotel industry and tourism management and proposes future research directions in this field. Research has shown that universities such as the Hong Kong Polytechnic University, the Harbin Institute of Technology, Sun Yat-sen University, and Nankai University have made significant academic contributions in this research field. Online reviews on travel websites, such as TripAdvisor, are the most commonly used data sources for this type of research, and scholars have paid particular attention to Beijing, Hong Kong, Shanghai, and Guangzhou, among other popular tourist cities. The predominant research topics include the perception of destination image, the impact of user-generated content on the performance of tourism enterprises, online reputation management of user-generated content, and incentive mechanisms for users’ online sharing behavior. In the future, it is expected that scholars will deepen and improve research in the field of tourism user-generated content in the Chinese context by probing the user-generated content of domestic tourists, employing management feedback strategies of domestic tourism enterprises, and exploring the user interaction modes of domestic homestay sharing platforms.

Keywords: tourism user-generated content; Chinese context; research progress; literature review

中图分类号:

叶强,梁赛,赵大营. 中国情境下旅游用户生成内容研究综述及展望[J]. 旅游导刊, 2021, 5(4): 16-36.

YE Qiang,LIANG Sai,ZHAO Daying. A Literature Review of Tourism User-Generated Content in the Context of China[J]. Tourism and Hospitality Prospects, 2021, 5(4): 16-36.

图/表 5

参考文献 70

[1]	Alonso-Almeida M D M, Borrajo-Millán F, Yi L. Are social media data pushing overtourism? The case of Barcelona and Chinese tourists[J]. Sustainability, 2019, 11(12):1~17.
[2]	Chen W, Gu B, Ye Q, et al. Measuring and managing the externality of managerial responses to online customer reviews[J]. Information Systems Research, 2019, 30(1):81~96.
[3]	Cheng V T P, Loi M K. Handling negative online customer reviews:The effects of elaboration likelihood model and distributive justice[J]. Journal of Travel & Tourism Marketing, 2014, 31(1):1~15.
[4]	Cheng X S, Fu S X, Sun J S, et al. An investigation on online reviews in sharing economy driven hospitality platforms:A viewpoint of trust[J]. Tourism Management, 2019(71):366~377.
[5]	Chiu C C, Chiu N H, Sung R J, et al. Opinion mining of hotel customer-generated contents in Chinese weblogs[J]. Current Issues in Tourism, 2015, 18(5):477~495.
[6]	Choi S, Lehto X Y, Morrison A M. Destination image representation on the web:Content analysis of Macau travel related websites[J]. Tourism Management, 2007, 28(1):118~129.
[7]	Chong A Y L, Khong K W, Ma T, et al. Analyzing key influences of tourists’ acceptance of online reviews in travel decisions[J]. Internet Research, 2018, 28(3):564~586.
[8]	Cong, Wu B, Morrison A M, et al. Analysis of wildlife tourism experiences with endangered species:An exploratory study of encounters with giant pandas in Chengdu,China[J]. Tourism Management, 2014(40):300~310.
[9]	Gong J H, Xie L S, Peng J M, et al. Customer responses to integrity issues for travel services in China:A content analysis based on online complaints[J]. International Journal of Contemporary Hospitality Management, 2015, 27(2):199~213.
[10]	Gu B, Ye Q. First step in social media:Measuring the influence of online management responses on customer satisfaction[J]. Production and Operations Management, 2014, 23(4):570~582.
[11]	Hou Z P, Cui F S, Meng Y H, et al. Opinion mining from online travel reviews:A comparative analysis of Chinese major OTAs using semantic association analysis[J]. Tourism Management, 2019(74):276~289.
[12]	Huang L. Social media as a new play in a marketing channel strategy:Evidence from Taiwan travel agencies’ blogs[J]. Asia Pacific Journal of Tourism Research, 2012, 17(6):615~634.
[13]	Hunter W C. China’s Chairman Mao:A visual analysis of Hunan province online destination image[J]. Tourism Management, 2013(34):101~111.
[14]	Hwang J, Park S, Woo M. Understanding user experiences of online travel review websites for hotel booking behaviours:An investigation of a dual motivation theory[J]. Asia Pacific Journal of Tourism Research, 2018, 23(4):359~372.
[15]	Kwok L, Xie K L. Buyer-seller similarity:Does it lead to a successful peer-to-peer transaction of room-sharing services?[J]. International Journal of Contemporary Hospitality Management, 2018, 30(9):2925~2944.
[16]	Li G, Law R, Vu H Q, et al. Discovering the hotel selection preferences of Hong Kong inbound travelers using the Choquet Integral[J]. Tourism Management, 2013(36):321~330.
[17]	Li G, Law R, Vu H Q, et al. Identifying emerging hotel preferences using emerging pattern mining technique[J]. Tourism Management, 2015(46):311~321.
[18]	Li H Y, Ye Q, Law R. Determinants of customer satisfaction in the hotel industry:An application of online review analysis[J]. Asia Pacific Journal of Tourism Research, 2013, 18(7):784~802.
[19]	Li H Y, Zhang Z L, Meng F, et al. “When you write review” matters:The interactive effect of prior online reviews and review temporal distance on consumers’ restaurant evaluation[J]. International Journal of Contemporary Hospitality Management, 2019, 31(3):1273~1291.
[20]	Li L, Lee K Y, Lee M, et al. Unveiling the cloak of deviance:Linguistic cues for psychological processes in fake online reviews[J]. International Journal of Hospitality Management, 2020(87):102468.
[21]	Li X, Wang Y C. China in the eyes of western travelers as represented in travel blogs[J]. Journal of Travel & Tourism Marketing, 2011, 28(7):689~719.
[22]	Li Y R, Lin Y C, Tsai P H, et al. Traveller-generated contents for destination image formation:Mainland China travellers to Taiwan as a case study[J]. Journal of Travel & Tourism Marketing, 2015, 32(5):518~533.
[23]	Liang S, Schuckert M, Law R. Multilevel analysis of the relationship between type of travel,online ratings,and management response:Empirical evidence from international upscale hotels[J]. Journal of Travel & Tourism Marketing, 2017, 34(2):239~256.
[24]	Liang S, Schuckert M, Law R. How to improve the stated helpfulness of hotel reviews? A multilevel approach[J]. International Journal of Contemporary Hospitality Management, 2019, 31(2):953~977.
[25]	Liang S, Schuckert M, Law R, et al. Be a “Superhost”:The importance of badge systems for peer-to-peer rental accommodations[J]. Tourism Management, 2017(60):454~465.
[26]	Liang S, Schuckert M, Law R, et al. The importance of marketer-generated content to peer-to-peer property rental platforms:Evidence from Airbnb[J]. International Journal of Hospitality Management, 2020(84):102329.
[27]	Liang S, Zhang Z L, Zhang Z Q, et al. Consumer motivation in providing high-quality information:Building toward a novel design for travel guide websites[J]. Asia Pacific Journal of Tourism Research, 2017, 22(6):693~707.
[28]	Liu X W, Law R. Insights into managers’ response behavior:Priority and effort[J]. International Journal of Hospitality Management, 2019(77):468~470.
[29]	Liu X W, Law R, Xu Y K. Does identity disclosure affect review extremity?[J]. Annals of Tourism Research, 2019(77):171~174.
[30]	Liu X W, Liu J W, Law R, et al. Power of profile name in online sharing[J]. International Journal of Hospitality Management, 2019(81):30~33.
[31]	Liu X W, Schuckert M, Law R. Can response management benefit hotels? Evidence from Hong Kong hotels[J]. Journal of Travel & Tourism Marketing, 2015, 32(8):1069~1080.
[32]	Liu X W, Schuckert M, Law R. Online incentive hierarchies,review extremity,and review quality:Empirical evidence from the hotel sector[J]. Journal of Travel & Tourism Marketing, 2016, 33(3):279~292.
[33]	Liu X W, Zhang Z L, Law R, et al. Posting reviews on OTAs:Motives,rewards and effort[J]. Tourism Management, 2019(70):230~237.
[34]	Liu Y, Huang K X, Bao J G, et al. Listen to the voices from home:An analysis of Chinese tourists’ sentiments regarding Australian destinations[J]. Tourism Management, 2019(71):337~347.
[35]	Liu Y, Teichert T, Rossi M, et al. Big data for big insights:Investigating language-specific drivers of hotel satisfaction with 412784 user-generated reviews[J]. Tourism Management, 2017(59):554~563.
[36]	Luo Q J, Zhong D X. Using social network analysis to explain communication characteristics of travel-related electronic word-of-mouth on social networking sites[J]. Tourism Management, 2015(46):274~282.
[37]	Park J K, Yang S J, Lehto X. Adoption of mobile technologies for Chinese consumers[J]. Journal of Electronic Commerce Research, 2007, 8(3):196~206.
[38]	Pearce P L, Wu M Y. Entertaining international tourists:An empirical study of an iconic site in China[J]. Journal of Hospitality & Tourism Research, 2018, 42(5):772~792.
[39]	Schuckert M, Liu X W, Law R. A segmentation of online reviews by language groups:How English and non-English speakers rate hotels differently[J]. International Journal of Hospitality Management, 2015(48):143~149.
[40]	Schuckert M, Liu X W, Law R. Insights into suspicious online ratings:Direct evidence from TripAdvisor[J]. Asia Pacific Journal of Tourism Research, 2016a, 21(3):259~272.
[41]	Schuckert M, Liu X W, Law R. Stars,votes,and badges:How online badges affect hotel reviewers[J]. Journal of Travel & Tourism Marketing, 2016b, 33(4):440~452.
[42]	Sparks B A, Perkins H E, Buckley R. Online travel reviews as persuasive communication:The effects of content type,source,and certification logos on consumer behavior[J]. Tourism Management, 2013(39):1~9.
[43]	Sun M H, Ryan C, Pan S. Assessing tourists’ perceptions and behaviour through photographic and blog analysis:The case of Chinese bloggers and New Zealand holidays[J]. Tourism Management Perspectives, 2014(12):125~133.
[44]	Sun M H, Ryan C, Pan S. Using Chinese travel blogs to examine perceived destination image:The case of New Zealand[J]. Journal of Travel Research, 2015, 54(4):543~555.
[45]	Sun S, Tong K T L, Law R. Chinese hotel guest perception of international chain hotels under the same hotel brand in different travel destinations:The cases of intercontinental and Sheraton[J]. Journal of Vacation Marketing, 2017, 23(2):172~188.
[46]	Tan H M, Lv X Y, Liu X Y, et al. Evaluation nudge:Effect of evaluation mode of online customer reviews on consumers’ preferences[J]. Tourism Management, 2018(65):29~40.
[47]	Tan W K, Chen T H. The usage of online tourist information sources in tourist information search:An exploratory study[J]. The Service Industries Journal, 2012, 32(3):451~476.
[48]	Tseng C, Wu B H, Morrison A M, et al. Travel blogs on China as a destination image formation agent:A qualitative analysis using Leximancer[J]. Tourism Management, 2015(46):347~358.
[49]	Wikipedia. User-generated content[EB/OL]. , 2019-07-10.
[50]	Wu J, Ma P H, Xie K L. In sharing economy we trust:The effects of host attributes on short-term rental purchases[J]. International Journal of Contemporary Hospitality Management, 2017, 29(11):2962~2976.
[51]	Wu M Y, Pearce P L. Chinese recreational vehicle users in Australia:A netnographic study of tourist motivation[J]. Tourism Management, 2014(43):22~35.
[52]	Wu M Y, Pearce P L. Tourism blogging motivations:Why do Chinese tourists create little “Lonely Planets”?[J]. Journal of Travel Research, 2016, 55(4):537~549.
[53]	Wu M Y, Wall G, Pearce P L. Shopping experiences:International tourists in Beijing’s silk market[J]. Tourism Management, 2014(41):96~106.
[54]	Xie K R, Mao Z X, Wu J. Learning from peers:The effect of sales history disclosure on peer-to-peer short-term rental purchases[J]. International Journal of Hospitality Management, 2019(76):173~183.
[55]	Yang F X. Effects of restaurant satisfaction and knowledge sharing motivation on eWOM intentions:The moderating role of technology acceptance factors[J]. Journal of Hospitality & Tourism Research, 2017, 41(1):93~127.
[56]	Yang Y, Park S, Hu X B. Electronic word of mouth and hotel performance:A meta-analysis[J]. Tourism Management, 2018(67):248~260.
[57]	Ye Q, Law R, Gu B. The impact of online user reviews on hotel room sales[J]. International Journal of Hospitality Management, 2009, 28(1):180~182.
[58]	Ye Q, Li H Y, Wang Z S, et al. The influence of hotel price on perceived service quality and value in e-tourism:An empirical investigation based on online traveler reviews[J]. Journal of Hospitality & Tourism Research, 2014, 38(1):23~39.
[59]	Zhang K, Chen Y, Li C L. Discovering the tourists’ behaviors and perceptions in a tourism destination by analyzing photos’ visual content with a computer deep learning model:The case of Beijing[J]. Tourism Management, 2019(75):595~608.
[60]	Zhang Z L, Liang S, Li H Y, et al. Booking now or later:Do online peer reviews matter?[J]. International Journal of Hospitality Management, 2019(77):147~158.
[61]	Zhang Z Q, Ye Q, Law R, et al. The impact of e-word-of-mouth on the online popularity of restaurants:A comparison of consumer reviews and editor reviews[J]. International Journal of Hospitality Management, 2010, 29(4):694~700.
[62]	Zhang Z Q, Zhang Z L, Law R. Positive and negative word of mouth about restaurants:Exploring the asymmetric impact of the performance of attributes[J]. Asia Pacific Journal of Tourism Research, 2014, 19(2):162~180.
[63]	Zhang Z Q, Zhang Z L, Wang F, et al. Factors influencing the effectiveness of online group buying in the restaurant industry[J]. International Journal of Hospitality Management, 2013(35):237~245.
[64]	Zhang Z Q, Zhang Z L, Yang Y. The power of expert identity:How website-recognized expert reviews influence travelers’ online rating behavior[J]. Tourism Management, 2016(55):15~24.
[65]	Zhao X Y, Wang L, Guo X, et al. The influence of online reviews to online hotel booking intentions[J]. International Journal of Contemporary Hospitality Management, 2015, 27(6):1343~1364.
[66]	Zhou L Q, Ye S, Pearce P L, et al. Refreshing hotel satisfaction studies by reconfiguring customer review data[J]. International Journal of Hospitality Management, 2014(38):1~10.
[67]	Zhu F, Zhang X Q. Impact of online consumer reviews on sales:The moderating role of product and consumer characteristics[J]. Journal of Marketing, 2010, 74(2):133~148.
[68]	江积海, 李琴. 平台型商业模式创新中连接属性影响价值共创的内在机理——Airbnb的案例研究[J]. 管理评论, 2016, 28(7):252~260.
	[JIANG Jihai, LI Qin. Effect of connection attributes of platform-based business model innovation on value co-creation based on case study of Airbnb[J]. Management Review, 2016, 28(7):252~260.]
[69]	李实, 叶强, 李一军, 等. 中文网络客户评论的产品特征挖掘方法研究[J]. 管理科学学报, 2009, 12(2):142~152.
	[LI Shi, YE Qiang, LI Yijun, et al. Mining features of products from Chinese customer online reviews[J]. Journal of Management Sciences in China, 2009, 12(2):142~152.]
[70]	余航, 田林, 蒋国银, 等. 共享经济:理论建构与研究进展[J]. 南开管理评论, 2018, 21(6):37~52.
	[YU Hang, TIAN Lin, JIANG Guoyin, et al. Sharing economy:Theory and research agenda[J]. Nankai Business Review, 2018, 21(6):37~52.]

排名 Ranking	期刊名称 Journal Name	论文篇数 Amount	占比（%） Proportion	影响因子（2018年） Impact Factor（2018）
1	Tourism Management	19	31.58	6.012
2	International Journal of Hospitality Management	12	21.05	4.465
3	International Journal of Contemporary Hospitality Management	8	14.04	3.957
4	Asia Pacific Journal of Tourism Research	7	12.28	1.444
4	Journal of Travel & Tourism Marketing	7	12.28	2.988
6	Journal of Hospitality & Tourism Research	3	5.26	2.849
7	Journal of Travel Research	2	3.51	5.338

排名 Ranking	期刊名称 Journal Name	论文篇数 Amount	占比（%） Proportion	影响因子（2018年） Impact Factor（2018）
1	Tourism Management	19	31.58	6.012
2	International Journal of Hospitality Management	12	21.05	4.465
3	International Journal of Contemporary Hospitality Management	8	14.04	3.957
4	Asia Pacific Journal of Tourism Research	7	12.28	1.444
4	Journal of Travel & Tourism Marketing	7	12.28	2.988
6	Journal of Hospitality & Tourism Research	3	5.26	2.849
7	Journal of Travel Research	2	3.51	5.338

排名 Ranking	核心机构 Core Institution	地区 Region	贡献频率 Contribution Frequency
1	香港理工大学	香港,中国	34
2	哈尔滨工业大学	哈尔滨,中国	21
3	中山大学	广州,中国	8
4	南开大学	天津,中国	6
5	詹姆斯库克大学	汤斯维尔,澳大利亚	5
5	浙江大学	杭州,中国	5
7	丹佛大学	丹佛,美国	4
7	南京审计大学	南京,中国	4
9	北京大学	北京,中国	3
10	加州州立理工大学波莫纳分校	波莫纳,美国	2
10	迪肯大学	墨尔本,澳大利亚	2
10	普渡大学	西拉法叶,美国	2
10	天普大学	费城,美国	2
10	内华达大学拉斯维加斯分校	拉斯维加斯,美国	2
10	怀卡托大学	汉密尔顿,新西兰	2
10	武汉大学	武汉,中国	2
10	元智大学	台湾,中国	2

排名 Ranking	核心机构 Core Institution	地区 Region	贡献频率 Contribution Frequency
1	香港理工大学	香港,中国	34
2	哈尔滨工业大学	哈尔滨,中国	21
3	中山大学	广州,中国	8
4	南开大学	天津,中国	6
5	詹姆斯库克大学	汤斯维尔,澳大利亚	5
5	浙江大学	杭州,中国	5
7	丹佛大学	丹佛,美国	4
7	南京审计大学	南京,中国	4
9	北京大学	北京,中国	3
10	加州州立理工大学波莫纳分校	波莫纳,美国	2
10	迪肯大学	墨尔本,澳大利亚	2
10	普渡大学	西拉法叶,美国	2
10	天普大学	费城,美国	2
10	内华达大学拉斯维加斯分校	拉斯维加斯,美国	2
10	怀卡托大学	汉密尔顿,新西兰	2
10	武汉大学	武汉,中国	2
10	元智大学	台湾,中国	2

平台名称 Platform Name	频率 Frequency	平台数据类型 Data Type	平台所属地域 Region
TripAdvisor	15	在线评论	美国
携程网	10	在线评论	中国
去哪儿网	5	在线评论	中国
小猪短租	4	在线评论	中国
大众点评网	3	在线评论	中国
到到网（TripAdvisor中文官网）	3	在线评论	中国
新浪博客、微博	3	博客、微博	中国
TravelPod（已关闭）	3	博客	美国
Airbnb	2	在线评论	美国
订餐小秘书	2	在线评论	中国
Virtualtourist（已关闭）	2	博客	美国

中国情境下旅游用户生成内容研究综述及展望

A Literature Review of Tourism User-Generated Content in the Context of China

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参考文献 70

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Metrics

排名 Ranking	城市名称 City Name	出现频率 Frequency
1	北京	16
2	香港	15
3	上海	8
4	广州	6
5	杭州	3
5	台湾	3
7	成都	2
7	澳门	2
7	三亚	2
7	西安	2

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[6]	郑伟民,李梦玲,庄歆怡,高胜男. 手机基站定位数据在旅游领域的应用综述[J]. 旅游导刊, 2021, 5(4): 37-57.
[7]	王佳果,郑密,黄琼慧,吴忠军. 文化距离何以影响旅游者?——文献反思与研究展望[J]. 旅游导刊, 2021, 5(3): 1-37.
[8]	刘林艳,张茵,靳杨楠. 基于理论应用视角的会展与节事研究述评[J]. 旅游导刊, 2021, 5(2): 1-34.
[9]	刘必强,黎耀奇. 所见即所得：旅游眼动研究述评与展望[J]. 旅游导刊, 2021, 5(1): 76-102.
[10]	隋新玉,刘兴双,王慧. 国内森林旅游核心问题研究进展及趋势[J]. 旅游导刊, 2020, 4(2): 77-95.
[11]	张燕, 章杰宽. 基于Web of Science 数据库的旅游业能源消耗研究综述及启示[J]. 旅游导刊, 2018, 2(2): 75-92.
[12]	孙鑫, 汪侠, 刘丹丽, 何静. 基于文献计量分析法的国内外旅游扶贫研究现状与展望[J]. 旅游导刊, 2017, 1(5): 55-67.
[13]	刘祥艳, 蒋依依, 吕兴洋. 中国出境旅游研究进展与展望[J]. 旅游导刊, 2017, 1(3): 65-79.
[14]	杨嫚, 刘泽华, 张瑜, 郑艺, 章锦河. 我国黄金周假日旅游研究的回顾与展望[J]. 旅游导刊, 2017, 1(3): 80-99.