方法对比

	Travel Community Netnography	Hospitality eWOM Analysis
领域	Tourism	Tourism
方法族	Process / pipeline	Process / pipeline
起源年份	2002	2008
提出者	Robert V. Kozinets	Stephen Litvin, Ronald Goldsmith & Bing Pan
类型	Adapted ethnographic pipeline for studying online communities	Framework and pipeline for measuring electronic word-of-mouth volume, valence and influence
开创性文献	Kozinets, R. V. (2002). The Field Behind the Screen: Using Netnography for Marketing Research in Online Communities. Journal of Marketing Research, 39(1), 61-72.	Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic Word-of-Mouth in Hospitality and Tourism Management. Tourism Management, 29(3), 458-468.
别名	Online Travel Community Ethnography, Tourism Netnography, Travel Forum Netnographic Analysis, Digital Travel Community Ethnography	Electronic Word-of-Mouth Analysis, Online Review Influence Analysis, Hospitality Online WOM Measurement, Digital Word-of-Mouth Analytics
相关	4	4
摘要	Travel community netnography applies netnography, ethnography adapted to the study of online communities, to the forums, social-media groups, blogs and review communities where travellers gather to share experiences, advice and meaning. Developed by Robert Kozinets (2002, 2010), netnography offers a rigorous, ethically grounded set of procedures for entering an online community, immersing in its communications, and interpreting the symbolism, meanings and consumption practices of its members. In tourism it is used to understand how travellers construct destinations, make decisions, perform identity and form attachments through naturally occurring online interaction, observed unobtrusively rather than provoked by an interviewer. Kozinets positioned netnography as faster, less costly and more naturalistic than offline ethnography while demanding the same interpretive depth, reflexivity and ethical care.	Hospitality eWOM analysis is the systematic study of electronic word-of-mouth, the consumer-generated reviews, ratings, posts and comments that travellers share online about hotels, restaurants, attractions and destinations. Litvin, Goldsmith and Pan (2008) set out the foundational framework, defining eWOM, classifying its channels by communication scope and level of interactivity, and explaining why it matters so much in hospitality and tourism, whose intangible products are difficult to evaluate before consumption and are therefore judged heavily through the experiences of others. The analysis treats this online word-of-mouth as data, measuring its volume, its valence (how positive or negative it is) and the experience dimensions it reveals, and links these to outcomes such as bookings, satisfaction and reputation. Xiang and colleagues (2015) showed how large-scale text analytics of guest-generated reviews can deconstruct the hotel experience and connect it to satisfaction.