Apr 5, 2011 - hotel brand, on the information that hotels provide and some reviews ... as Tripadvisor.com, Hotels.com, Wotif.com.au, Expedia.com and others ...
Book of Proceedings
Brand, Identity and Reputation: Exploring, Creating New Realities and Fresh Perspectives on Multi-Sensory Experiences
7th Global Brand Conference of the Academy of Marketing‘s
Brand, Corporate Identity and Reputation SIG
April 5th – 7th 2011 Said Business School, University of Oxford, UK
1
―There was a Cockroach in my Room‖ – an Analysis of Customer Feedback on Hotel Booking Websites as an Example of Co-creation of Meaning Petra Bouvain, University of Canberra, Australia Matthias Muskat, University of Canberra, Australia Brigit Muskat, University of Canberra, Australia Introduction The tourism industry has undergone fundamental changes in the way that customers obtain information and the way that they book their holidays. Providing information about destinations, flights and hotels via the Internet is now considered standard practice. Most hotels have a website that promotes their property and provides information about the amenities that are offered, in most cases augmented by the display of photos, downloadable brochures and videos. The accommodation providers range from multinationals to SMEs and micro businesses. Branding and reputation can be considered a key resource for SMEs (Abimbola & Kocak, 2007). Most hotel sites offer customers also the possibility to book online and to communicate via email. Customers have relied in their decision making on the reputation of the hotel brand, on the information that hotels provide and some reviews that may have been undertaken by third parties such as travel guidebooks like the Michelin guide books or Lonely Planet. Purpose of the Paper The paper shows how the emergence of Web2.0 has changed the nature of the interaction between hotels and consumers and explores how word of mouth is amplified via new intermediaries. Consumers are now able to not only communicate via email with tourism providers but are able to share views and experiences with other consumers via Twitter and Facebook. Consumers now trust their peers more than they do trust the information provided by corporations. The increasing amount of user-generated content in marketing websites changes the way that decisions are made and in this context the impact of trust buyer-seller relationship has been discussed in marketing as well as in organisational studies (Chang & Chen, 2008; Ganesan & Hess, 1997; Kim, Chung, & Lee, 2010; Morgan & Hunt, 1994; Zhu & Zhang, 2010). The expectation of customers is that information provided by peers is more trustworthy. A study by Forrester Research showed that reviews/ratings are considered to have the highest share of influence (32%) followed by discussion forums (29%), blog comments (24%) and blog posts (16%). Facebook is considered to have the highest share of influence (62%) of all social networking sites (Forrester Research, 2010). Word of mouth has long been considered one of the most trusted sources of information and marketers in the hospitality and tourism management sector are looking at strategies to manage and influence user-generated content social media as part of integrated marketing communication strategies (Litvin, Goldsmith, & Pan, 2008; McConnell & Huba, 2007; Xiang & Gretzel, 2010). Consumers are increasingly looking for information to aid decision making from their peers and no longer rely on promotional material provided by the company. This changing behaviour is having an impact of how customers are targeted depending on their engagement within social networks (Nielsen, 2009). Shao (2009) examines the appeal of user generated media and concludes that consumers perceive as one of the core benefits the obtaining of information, but also points out that there is an element of entertainment included in the experience while consumers engage in blogging, twitting, document sharing and posting of information. All these Internet activities enable consumers to obtain a collective intelligence (Litvin et al., 2008). While individual comments may be somewhat helpful the sum of the comments provides a broad spectrum of opinions, aided by information about the provider of the feedback. Different sites provide varying background information on the contributors, categorised as business traveller, couples, families with children and country of origin of the traveller. The rapid growth of hotel feedback sites is increasingly important in international hotel marketing, as potential visitors are more and more using these web-sites as their main source of information (Buhalis, 2003). Positive comments tend to be viewed by customers as more helpful when compared to negative comments when deciding to book accommodation (Black & Kelley, 2009). The expertise of the reviewer, familiarity with the hotel brand and the sentiment of the review (positive or negative in nature) referred to by Vermeulen and Seegers (2009) as review valence have been shown in an experimental study to have an influence on consumer choices, which is not surprising, but the interesting fact was that both positive and negative reviews had an influence on consumers considering a particular hotel (Vermeulen & Seegers, 2009). There is some evidence that shows the impact of customer feedback on room occupancy rates which has been explored in a regression model of a Chinese travel site by Ye, Law and Gu (2009). The study showed that positive feedback had a positive impact on room sales, which again could be expected. However the study did not have access to actual room sales data, but provides, by using proxies, some interesting insights into the effects of online feedback on hotel bookings. A number of studies (Bonn, Furr, & Susskind, 1998; Weber & Roehl, 1999) examined the demographic characteristics of online booking customers and they found that online customers have higher education levels and are between 25 and 55 years of age. This finding has been supported by data obtained from Alexa.com in 2010. Murphy et al. have been one of the early researchers that examined the factors that were more likely to lead to bookings on online hotel booking sites (Murphy, Forrest, Wotring, & Byrmer, 1996). Kim and Kim (2004) investigated the factors that make online
170
booking attractive in greater detail. Yoon conducted an experimental study that explored factors such as navigation and layout and its impact on satisfaction (Yoon, 2002). The emergence of web-based hotel ratings has introduced new intermediaries in the tourism industry. Internet sites such as Tripadvisor.com, Hotels.com, Wotif.com.au, Expedia.com and others provide information mainly sourced from the hotel operators and now in increasing numbers ratings and comments from people who have stayed at the hotels. Hotels are adjusting their marketing to take account of this new situation. An example of this is the decision by the Accor Group, owners of well known brands such as Novotel and Mercure, to provide a link on their website to allow customers to access feedback from Tripadvisor conveniently. This offers the aided advantage that customers do not need to switch to the Tripadvisor site in order to get the comments, with the risk that the potential customer may be enticed to look at offerings from other hotels. The emergence ofOther initiatives are linked to social online-networks such as Twitter.com, Youtube.com and Facebook.com with both hotel booking sites and hotels developing corporate sites on these social networking sites to engage with customers. Prahalad introduced the concept of co-creation of value and meaning, which outlines how brands and products are no longer solely created by organisations, but in a symbiotic process between customers and providers (Prahalad & Ramaswamy, 2004). In this paper we show how this symbiotic relationship is developing in the tourism industry. Design/Methodology In order to determine the most popular sites for hotel feedback we have used two different methods. The first one was to look at Google rankings for hotel booking sites. We used two search words, hotel ranking and hotel rating, and used both singular and plural for those. This list included both sponsored research results as well as natural results. Based on this list we used the web analysis tool Alexa to determine which sites were the most popular and most visited ones. Alexa provides, based on web crawls and user installed toolbars, the ability to assess the popularity of websites (alexa.com). We complemented this data with data obtained from Experian Hitwise (hitwise.com). Alexa also provides information about the kind of traffic that the sites receive and we have incorporated this information in our research. We then examined those companies further and looked at their ownership structure, annual reports and financial data, using the MINT Global database (mintglobal.bvdep.com). We decided to explore the five most popular sites, Tripadvisor.com, Expedia.com, Priceline.com, Bookings.com and Orbitz.com in detail and analysed the top 5 rated hotels in Sydney on all five sites. We chose for each hotel the most recent 50 comments, as research suggests that customers rarely view comments beyond the first 3 pages (Pavlou & Dimoka, 2006). For this reason we deemed it best to concentrate on more recent comments, which the systems lists first (no older than 6 months), to provide a fair comparison. We then analysed those comments using an analysis tool called Leximancer that enables us to perform a conceptual text analysis. We modelled on content analysis and seeded concept classifiers (Smith, 2003; Smith & Humphreys, 2006) to look at themes that were either specific to each hotel, or those that were universal and seemed important in the sum of feedback to provide an insight into the nature of comments by customers. Using software to identify the themes is a less subjective process than relying on human judgement and thus avoids the temptation by the coder to overrate some comments that trigger a strong emotional response, such as the presence of cockroaches in a hotel room. Results The Leximancer analysis has revealed the key themes that contribute to positive and negative reviews. We hypothesise that conventions are emerging in terms of who can rate, what items are rated and how the process will be moderated to weed out fraud. Other industry sectors will benefit from these developments to enable them to provide robust feedback to customers. References 1. Alexa.com, Internet resource, URL http://www.alexa.com/, retrieved 20 October 2010. 2. Abimbola, T., & Kocak, A. (2007). Brand, organization identity and reputation: SMEs as expressive organizations: A resources-based perspective. Qualitative Market Research: An International Journal, 10(4), 416-430. doi:10.1108/13522750710819748. 3. Black, H.G., & Kelley, S.W. (2009). A storytelling perspective on online customer reviews reporting service failure and recovery. Journal of Travel & Tourism Marketing, 26(2), 169-179. doi:10.1080/10548400902864768. 4. Bonn, M.A., Furr, H.L., & Susskind, A.M. (1998). Using the Internet as a pleasure travel planning tool: An examination of the sociodemographic and behavioral characteristics among Internet users and nonusers. Journal of Hospitality & Tourism Research, 22(3), 303. doi:10.1177/109634809802200307. 5. Buhalis, D. (2003). eTourism: Information Technology for strategic tourism management. London: Prentice Hall. doi:10.1016/j.tourman.2008.01.005. 6. Chang, H.H., & Chen, S.W. (2008). The impact of online store environment cues on purchase intention: trust and perceived risk as a mediator. Online Information Review, 32(6), 818-841. doi:10.1108/14684520810923953. 7. Forrester Research (2010). State of online word of mouth. Mashable at Http://mashable.com/2010/04/25/word-of-mouth-stats/, retrieved October 2010. 8. Ganesan, S., & Hess, R. (1997). Dimensions and Levels of Trust: Implications for Commitment to a Relationship. Marketing Letters, 8(4), 439-448. doi: 10.1023/A:1007955514781. 9. Experian Hitwise, Internet resource, URL http://www.hitwise.com/, retrieved 20 October 2010. 10. Kim, M.J., Chung, N., & Lee, C.K. (2010). The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea. Tourism Management, 32(2), 256- 265. no doi available. 11. Kim, W.G., & Kim, D.J. (2004). Factors affecting online hotel reservation intention between online and non-online customers. Internatioanl Journal of Hospitality Management, 23, 381-395. doi:10.1016/j.ijhm.2004.02.001. 12. Litvin, S.W., Goldsmith, R.E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29, 458-468. doi:10.1016/j.tourman.2007.05.011. 13. McConnell, B., & Huba, J. (2007). Citizen marketers: When People are the Message. Chicago: Kaplan.
171
14. MINT Global, Internet resource, URL https://mintglobal.bvdep.com/version-201131/Home.serv?product=mintglobal&loginfromcontext=ipaddress, retrieved 20 October 2010. 15. Morgan, R.M., & Hunt, S.D. (1994). The Commitment Trust Theory of Relationship Marketing. Journal of Marketing, 58(July), 20-38. no doi available. 16. Murphy, J., Forrest, E.J., Wotring, C.E., & Byrmer, R.A. (1996). Hotel management and marketing on the Internet: an analysis of sites and features. The Cornell Hotel and Restaurant Administration Quarterly, 37(3), 70-82. doi: 10.1177/001088049603700322. 17. Nielsen (2009). Global Faces and Network Places. A Nielsen report on social networking's new global footprint, http://blog.nielsen.com/nielsenwire/global/social-networking-new-global-footprint/, retrieved on 5.11.2010. 18. Pavlou, P.A., & Dimoka, A. (2006). The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentation. Information Systems Research, 17(4), 392-414. doi 10.1287/isre.1060.0106. 19. Prahalad, C.K., & Ramaswamy, V. (2004). Co-creating unique value with customers. Strategy & Leadership, 32(3), 4-9. doi:10.1108/10878570410699249. 20. Shao, G. (2009). Understanding the appeal of user-generated media: a uses and gratification perspective. Internet Research, 19(1), 7-25. doi:10.1108/10662240910927795 21. Smith, A.E. (2003). Automatic Extraction of Semantic Networks from text using Leximancer. Paper presented at the Proceedings of HLT. doi:10.3115/1073427.1073439. 22. Smith, A.E., & Humphreys, M.S. (2006). Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping. Behavior Research Methods, 38(2), 262-279. doi:10.3758/BF03192778. 23. Vermeulen, I.E., & Seegers, D. (2009). Tried and tested: The impact of online hotel reviews on consumer consideration. Tourism Management, 30(1), 123127. doi:10.1016/j.tourman.2008.04.008. 24. Weber, K., & Roehl, W.S. (1999). Profiling people searching for and purchasing travel products on the World Wide Web. Journal of Travel Research, 37(3), 291-298. doi: 10.1177/004728759903700311. 25. Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management, 31(2), 179-188. doi:10.1016/j.tourman.2009.02.016. 26. Ye, Q., Law, R., & Gu, B. (2009). The impact of online user reviews on hotel room sales. International Journal of Hospitality Management, 28, 180-182. doi:10.1016/j.ijhm.2008.06.011. 27. Yoon, S.J. (2002). The antecedents and consequences of trust in online-purchase decisions. Journal of Internactive Marketing, 6(2), 47-63. doi:10.1002/dir.10008. 28. Zhu, F., & Zhang, X. (2010). Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics. Journal of Marketing, 74(3), 133-148. doi: 10.1509/jmkg.74.2.133.
172
