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The Digitization of Word-of-Mouth

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Social Media Marketing in Tourism and Hospitality

Abstract

From the first article published on the topic of electronic word-of-mouth (eWOM) research has rapidly increased, underlining the importance of this phenomenon in various business contexts. Customers’ purchasing behavior has increasingly changed with the development of Information and Communication Technologies and social media. Therefore, what had traditionally been defined as word-of-mouth (WOM) needs to be reconsidered and studied in light of recent trends. This chapter will analyze the evolution of the concept from WOM to eWOM and main dimensions for an analysis of WOM. Specific attention will be paid to credibility and possible biased information.

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Notes

  1. 1.

    Social ties can be classified as strong or weak (Granovetter 1973). Strong ties are represented by closer relationships with the individual’s social network such as family and friends. On the other hand, weak ties are generally weaker and less personal social relationships that facilitate the information search about a specific topic (such as colleagues). According to Duhan et al. (1997) a tie can be characterized by various degrees of strength: it is weak if the recommender is just an acquaintance or is not known to the consumer and it is strong when the consumer knows the recommender personally. For an authoritative analysis of this topic, see also Pigg and Crank (2004), Gruen et al. (2006), and Chu and Kim (2011).

  2. 2.

    According to Rosen (2000) we are moving from “old” online buzz mainly text-based to the new visual buzz based on images.

  3. 3.

    Actually, before the development of IT and online review sites, it was possible to publish a written product review on specific magazines; for example, the magazine of a consumers’ association.

  4. 4.

    Godes and Mayzling (2009) use the term “exogenous WOM” to describe the proactive actions of companies which induce their consumers to spread the word about their products online (Godes and Mayzlin 2004, 2009).

  5. 5.

    Viral marketing will be analyzed in Chap.4.

  6. 6.

    For a literature review on the topic of dual process theories, see Gawronski and Creighton (2013).

  7. 7.

    Banerjee and Chua (2014) identify two types of misleading reviews: disruptive and deceptive. Disruptive reviews refer to messages that “are frivolous and contain unmistakably irrelevant text,” while deceptive reviews concern messages that “are maliciously written to appear genuine, and hence not easily detected as spam”.

  8. 8.

    Anonymity can be reduced through personal identifying information (PII) (Xie et al. 2011).

  9. 9.

    Companies have been created recently with the specific aim to produce and sell fake reviews to travel companies. UK and U.S. public authorities have started to intervene through specific legal actions (see Sect. 2.7.1).

  10. 10.

    An interesting stimulus for future research is offered by Mayzlin et al. (2012) who found that independent hotels engage more than multi-unit branded hotels in reviews manipulation.

  11. 11.

    Online consumers’ reviews are generally composed by a numerical rating of the product, a textual message, and visual content (i.e., photos, videos).

  12. 12.

    Contradictory to prior research, a recent study of Banerjee and Chua (2014) found that genuine reviews contain fewer self-references than deceptive reviews.

  13. 13.

    Mauri (2002) identifies the following dimensions for the analysis of word-of-mouth: valence (positive and negative); intensity (quantity of comments); speed (number of contacts in certain period of time); persistency (length in time); importance (role of comments in the customer decision-making process); credibility (in terms of assurance and confidence of the source of the message).

  14. 14.

    Dual process theory considers how different types of influences affect the persuasiveness of online consumer reviews. Informational influence depends on the content of the message (central route factors), while normative influence concerns the impact of online social aggregation mechanisms (peripheral route factors) (Petty and Cacioppo 1984; Cheung et al. 2009).

  15. 15.

    Bambauer-Sachse and Mangold (2011) confirm the same result, also in the case in which the customer is familiar with the brand.

  16. 16.

    According to Grönroos (1982) WOM is a key factor that influences expected quality along with marketing communication, company image, price, and customers’ needs and values. Perceived quality is then the result of the comparison between expected quality and experienced quality (Grönroos 1982; Oliver 1980, 1993; Parasuraman et al. 1985; Lovelock and Wright 1999).

  17. 17.

    Doh and Hwang (2009) demonstrate that a perfect set of positive messages is not required to influence receivers’ behaviors.

  18. 18.

    Recency refers to the date the review was posted. Recent reviews influence more strongly the popularity rankings while older reviews have less impact on a hotel’s ranking over time. See more at: http://www.tripadvisor.com/TripAdvisorInsights/n543/how-improve-your-popularity-ranking-tripadvisor#sthash.Xw6o9uKR.dpuf.

  19. 19.

    O’Connor (2010) applied the criteria suggested by Keates (2007) for the identification of false reviews (namely extreme scores and a solitary visit by the reviewer to join and post the review). In the same way, an experimental study of Mukherjee et al. (2013) demonstrates that Yelp filtering is reliable.

  20. 20.

    For further insights see New York State office of Attorney General, 23rd September 2013: Available via: http://www.ag.ny.gov/press-release/ag-schneiderman-announces-agreement-19-companies-stop-writing-fake-online-reviews-and.

  21. 21.

    See the response of TripAdvisor to the studies on fake reviews. Available at: http://www.tnooz.com/article/tripadvisor-responds-to-provocative-study-of-bogus-online-reviews/#sthash.Qh6fAER6.dpuf

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  1. Department of Law, Economics and Cultures, University of Insubria, Como, Italy

    Roberta Minazzi

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Correspondence to Roberta Minazzi .

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Minazzi, R. (2015). The Digitization of Word-of-Mouth. In: Social Media Marketing in Tourism and Hospitality. Springer, Cham. https://doi.org/10.1007/978-3-319-05182-6_2

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