Responses to Consumer Generated Media in the Hospitality Marketplace: An Empirical Study
Stephen W. Litvin Professor, Hospitality & Tourism Management School of Business College of Charleston Charleston, SC 29424
[email protected] Laura M. Hoffman Honor’s College Graduate Hospitality & Tourism Management School of Business College of Charleston
[email protected]
This is the final draft of the paper, published in JVM. Please cite as Litvin, S.W. and Hoffman, L.M. (2012). “Responses to Consumer Generated Media in the Hospitality Marketplace: An Empirical Study.” Journal of Vacation Marketing, Vol. 18 (2): 135-146 See JVM for published article.
2 Responses to Consumer Generated Media in the Hospitality Marketplace: An Empirical Study Abstract:
Consumer generated media (CGM) has become a significant force in the hospitality marketplace. This paper reports the results of an experiment that was conducted to determine the moderating affect of consumer rebuttals and management responses to negative postings on travel review boards. The results suggest that potential hotel guests react more favorably to a rebuttal of a negative review posted by a fellow traveler than they do to a response posted by hotel management; but that both have the power to positively influence consumer attitudes towards the property. Managerial suggestions are provided.
Key words: social media, service recovery, CGM, electronic word-of-mouth, WOM
3 RESPONSES TO CONSUMER GENERATED MEDIA IN THE HOSPITALITY MARKETPLACE: AN EMPIRICAL STUDY
INTRODUCTION
Before the dawn of social media, consumers, whether disgruntled or delighted, could inform a relatively small number of others of their travel experience. Today, through sites such as Yelp and TripAdvisor, which boasts 20 million members and over 40 million reviews and opinions (TripAdvisor.com 2011), as well as via consumer review pages found on virtually all on-line booking-sites (Expedia, Travelocity, Hotels.com, etc.), travelers can share their first-hand commentaries and personal raves, rants and ratings with the world (Jeong & Jeon 2008).
Enabled by the advent of Web 2.0 technologies, consumer generated media [CGM] has allowed tourism markets to become “real conversations…taking the small contributions of millions and making them matter” (Milano, Baggio & Piattelli 2011: 2). The result, Grossman (2006) notes, has been a changing marketplace within which ‘the many’ has wrestled power from ‘the few.’ While many, perhaps most, posted CGM review comments hold little value to the average site-user, others resonate as on-target and useful (Yoo & Gretzel 2010; Yoo, et al. 2009). As noted by Locke et al. (2000) a decade ago: “people in networked markets have figured out that they get far better information and support from one another than from vendors.” And while CGM is “often unstructured, indeed quirky and random” (Akehurst 2009: 2), providing “a mixture of fact and opinion, impression and sentiment, founded and unfounded tidbits, experiences, and even rumor” (Blackshaw & Nazzaro, 2006: 4), it is difficult to argue that CGM has fundamentally reshaped the way people plan for and consume travel (Buhalis & Law 2008). The research that follows adds to our exploration of emerging CGM issues and provides guidance to tourism management and marketers as they attempt to best utilize CGM for their benefit.
4 CGM and the Literature Today’s vacation travel consumers rely upon the internet during both their information seeking and conative stages of travel purchase, with CGM very often an instrumental part of the process (Bart et al. 2005). For providers, however, CGM presents both opportunities and threats (Yoo & Gretzel 2008) and it is increasingly apparent that tourism and travel marketers must have an appreciation and understanding of its power (Alikiliç 2008; Xiang & Gretzel 2010). As commented by Oser (2005), CGM has brought technology to the most basic form of communication, consumer-to-consumer (C2C), providing far flung travelers and potential travelers the ability to exchange opinions asynchronously, with postings having the potential to reach millions of viewers. CGM is of particular importance to the tourism industry, as travel is a ‘credence good’ (Shoemaker, Lewis & Yesawich 2007), i.e. a product or service that cannot be tested before purchase and is thus heavily reliant upon the input of others during the purchase decision-making process (Sun & Qu 2010). Litvin, Goldsmith and Pan (2008) have noted that CGM reviews provide a strong sense of the product, add to the consumer’s overall image of the hotel or destination, likely reduce pre-purchase doubt, and mitigate post-purchase dissonance. These authors postulate that the faceless reviewers who post their comments to review web-pages are rapidly becoming the travel opinion-leaders of the electronic age. Williams (2006) has made a similar argument, noting customers tend to trust CGM reviewers’ opinions even more than they do a travel agent working for commission. Taking this a step further, Frumkin (2007), perhaps overstating his case, has proclaimed the days of professional reviews over, with the reviews of amateurs via CGM the new standard. Pearse (2007:16) commented that TripAdvisor provides “the wisdom of crowds, good old word of mouth, call it what you will,” and predicts its continued importance in travel decision making. He further noted that consumers have learned to “distinguish between a moaner and someone with a good point” and that this ability to filter through postings provide companies less reason to fear the power of social media. Another study, the
5 annual Edelman Trust Barometer (Edelman 2011), noted that 43% of respondents found postings by ‘a person like yourself’ to be a credible source of information, versus 34% who trusted the word of a company employee. Given the above, it is not surprising that many current studies, to include Vermeulen and Seegers (2009), Ye, Law and Gu (2009), and Yoo and Gretzel (2008) have noted that positive reviews can lead to increased hotel bookings, while negative reviews can cause bookings to decrease.
Why would potential travelers be willing to rely upon unknown posters when forging their travel decisions, as doing so requires confidence in a world of anonymity (DeWitt, Nguyen and Marshall 2008)? This question is of particular importance when two situational factors are present: uncertainty (risk) and incomplete product information or information asymmetry (Ba & Pavlou 2002). The purchase of vacation travel is a high risk product with, given the complexity of the product and the infinite number of available options, consumers never having complete information. Any source, to include CGM, that a consumer perceives to help reduce uncertainty is therefore of value (Mukherjee and Nath 2007). And while a reader of CGM can never fully understand the motive of the person posting (Mack, Blose and Pan 2007), Yoo and Getzel (2010) have noted that the vast majority of CGM users (81%), while finding CGM less trustworthy than traditional word of mouth, do trust and are influenced by travel CGM postings. Yoo and Getzel (2010) observed that while there was much recent interest in the topic of confidence in travel websites and e-commerce vendors [see Yoo & Getzel 2010 for a comprehensive listing of articles], insufficient attention has been paid to the confidence placed by consumers in CGM. The research discussed below, conducted to add to that literature and extend our knowledge regarding CGM and travel, evaluates an aspect of CGM management not previously discussed in the hospitality and tourism literature – the effectiveness of consumer rebuttals and management responses to negative on-line comments within a CGM environment.
The work of Rajah, Marshall and Nam (2008), in a study that considered the role of travel agents in the booking of a vacation trip, determined that the strength of relationship
6 between the travel agent and the tourist during the planning process had a positive impact on the attitude of the consumer toward the travel seller, which in turn led to increased satisfaction and consumer loyalty. And, TravelMole, a practitioner newsletter recently advised its readers to “answer negative reviews, even if they don’t know who posted them” (Wilkening 2010). It would seem, given the increasing importance of CGM for travel purchasing, as discussed above, and in line with Rajah, Marshall and Nam’s (2008) research regarding provider involvement, that positive rebuttals to negative comments posted on CGM websites should increase potential visitor confidence in a hotel property, thus increasing purchase likelihood. But keeping up with the numerous websites and postings takes considerable work. Is such an effort worthwhile? The research described below, relatively exploratory in nature, seeks to answer this question. The findings should be of value to hospitality marketers as they consider their investment in the resources required to monitor CGM sites and the value of their riposte to negative commentaries. The specifics of the research conducted, a manipulation of hypothetical reviews in an experimental design, and the managerial implications of the study’s results follow.
RESEARCH METHOD
The method employed was a controlled experiment, administered via an online survey instrument. Participants were exposed to sets of on-line reviews of three fictitious midrange “3 star” hotels. These were dubbed the Plaza, the Vista and the Summit. CGM review pages for the three hotels were formatted to mimic TripAdvisor.com. Each review set encompassed three guest postings. As is often the case, these reviews were inconsistent. The first review for each property was neutral (the poster awarded the hotel 3 of 5 stars), the second was positive (4 of 5 stars), while the third was negative (1 of 5 stars). The overall TripAdvisor rating for each hotel was three stars. When crafting the three review sets, modified from actual review comments found on TripAdvisor, the intent was that each of the three properties would be viewed as reasonably equal in quality and reflective of a mid-tier hotel. To ensure these goals were accomplished, and to provide baseline results for the experiment, a pre-test was conducted.
7 The pre-test of the scenarios used in the main experiment encompassed 180 undergraduate students [the main test used adult consumers]. Pre-test participants were provided the three sets of hotel reviews. To avoid ‘order effect’ (Carlson, Meloy & Russo 2006), these were distributed in random order. Participants were asked to rate each property based upon the following three questions designed to measure their affective, cognitive and conative reactions to the property (as suggested by Back & Parks 2003):
1. How do you feel about this hotel? [Response options included 1=positive, 3=neutral, 5=negative.] 2. Do you think this hotel would provide service to meet your expectations? [Response options included 1=yes, 3=unsure, 5=no.] 3. Assuming for this trip you are looking for a “three-star” hotel, and this one fits your needs (budget, location, etc.), would this be a hotel you would consider booking? [Response options included 1=yes, 3=unsure, 5=no.]
Participation was voluntary and the response rate was approximately 50%. Cronbach Alpha’s for the three three-question sets confirmed reliability (weakest of the three alphas was 0.819), allowing responses to be summed for each property. The summed score means for the three properties ranged from 8.5 to 9.7 (maximum possible = 15 points). The mid-scale results were reasonable scores for a mid-level hotel, sufficiently consistent to allow analysis of the main findings, and established the base-line scores against which main-test treatments were measured.
Main test participants (described below) were asked to evaluate the three hotels utilizing the same three-question set employed in the pre-test, but with treatments added to the Vista and Summit reviews. The Vista’s review included the three guest comments from the pre-test plus an additional positive guest comment specifically rebutting the negative review that preceded it. The Summit’s review included the three guest comments, plus hotel management’s response to the negative comment. For sake of reliability testing, and to serve as a manipulation check, the Plaza remained unchanged from the pre-test. As with the pre-test, to avoid ‘order effect’, the on-line survey was programmed such that
8 participants were exposed to the three hotels in random order. The scenarios employed are appended. For the main-test, convenience sampling using the ‘snowball’ method was employed. Participants familiar to the researchers were recruited through email and social media networks, requesting their participation and asking that they forward the request to others. This approach resulted in an audience of significant size, and focused on those who used social media/email in their daily life – appropriate for a study based upon CGM. Maintest participants were directed to a university web-page where they found an invitation to participate, standard university Institutional Review Board comments, and a link to the survey instrument. In addition to the evaluative questions, demographic data were requested as were several enquiries related to the participant’s use of online review websites.
A total of 263 substantially complete survey responses were received. The average participant was 45 years of age (range 18-78). A disproportionate share (71%) was female. Most participants had at least some college education and 41% reported an undergraduate degree. The sample was predominantly (61%) ‘white collar.’ Asked if they had ever used an online travel review site, 80% responded affirmatively. Table 1 provides additional sample detail.
// Please insert Table 1 about here \\
RESULTS
The primary research question related to participant attitude towards the three hotels. The potential range for each treatment was 3 to 15 (three-question scale, each with a fivepoint Likert-like response option; as with the pre-test, these were found reliable with Alpha’s that ranged from 0.873 to 0.917). Response options were formatted such that the lower the score the more positive the attitude. The mean response for the Plaza Hotel, the hotel with no main-test treatment, was 9.9 (SD=2.9), a response statistically unchanged
9 from the pre-test result of 9.7 (SD=2.9; T=0.493, p=0.622). The main-test mean response for the Vista Hotel scenario, the hotel review that included the positive customer rebuttal, improved to 6.0 (SD=2.2), a very significant 29% improvement from the pre-test’s rating of 8.5 (SD=2.6; T=-8.528, p=0.000). Evaluation of the Summit Hotel, the property with management’s reply to the negative customer comment, also improved from its pre-test base-line rating, but far more modestly, improving 15% from a pre-test score of 9.2 (SD=2.6) to a main-test mean rating of 7.8 (SD=3.2; T=-3.685, p=0.000). (These findings are presented in tabular form, please see Table 2.)
// Please insert Table 2 about here \\
Demographics were interjected into the analysis to ensure these did not have a moderating effect upon the above results. Neither gender nor level of education influenced the ratings. Testing of gender was particularly important given the heavy female skew of the sample. The only statistically significant correlation noted was a very weak relationship between respondent age and the rating of the Vista Hotel (r=0.150, p=0.024). Given that for the other two hotels age was not a factor (r=0.026, p=-0.693 and r=-0.042, p=-0.539) and given the weakness of the one significant correlation, it seems likely that this result was not consequential. Future research, however, should seek to ensure that age does not in fact play a role in evaluating the impact of management responses to a negative review.
A finding of secondary importance related to the weight participants attributed to CGM versus traditional sources – hotel advertisements, recommendations from friends and family, professional reviews, and prior personal experience. Respondents rated these based upon a five-point scale that ranged from 1=“very influential” to 5=“not influential.” Prior personal experience was found to be most influential (mean=1.1, SD=0.5), followed by recommendations from friends and family (1.4, SD=0.6), online customer reviews (i.e. CGM) (2.3, SD=0.9), professional reviews (2.5, SD=1.0) and finally advertisements (3.1, SD=0.9). Respondents were also asked to rank these factors
10 from ‘most influential” to “least influential.” The rank order of the ordinal responses mirrored the interval responses.
DISCUSSION
This research found that managed CGM can significantly affect consumer attitudes, with potential guests displaying more favorable attitudes towards a hotel purchase decision when negative customer reviews are refuted by a positive customer review and, though less dramatically, when hotel management provides a response to a negative customer review.
CGM is by definition a customer driven force. The above findings point to the importance of getting one’s existing customers involved. Satisfied customers should be encouraged to post positive reviews. Perhaps a message such as ‘If you enjoyed your stay, please let others know by sharing your thoughts on TripAdvisor’ would make for an effective sign at a hotel’s front desk. In addition, a hotel checkout script might include a request encouraging guests to visit the on-line site they most often use to rate their stay. Loyal customers, with encouragement, can become advocates for the property. Their support, and specifically their willingness to counter negative comments, this study shows, can positively affect the attitudes of other potential guests.
Equally important is management becoming a part of the online conversation. Online review sites should be closely monitored. This will serve multiple purposes. First, and perhaps most importantly, reading negative reviews will help the property become more aware of problems when they occur. Hotels rely heavily upon traditional guest response cards as a tool to help optimize their service product. CGM review sites now provide a plethora of additional consumer responses; data free for the taking. To not be monitoring these closely is an opportunity missed. But beyond simply reading consumer postings, this research suggests that management should be actively responding to negative reviews, apologizing for shortcomings, explaining discrepancies, and discussing corrective actions taken or planned. Doing so opens a new line of communication with
11 potential guests, and demonstrates that management is dedicated to pleasing them. Craig (2010) has noted less than 4% of TripAdvisor.com negative reviews receive a management response. These findings suggest the industry is missing an opportunity by not responding. Not only will the comments of management improve the CGM user’s opinion of the property, they will also differentiate the property from the vast number of hotels that fail to do so.
It is also of interest to note the order respondents listed influencers of their hotel selection decision-making. That prior experience and personal recommendations were most important is certainly not surprising, but the fact that on-line reviews, for these respondents, eclipsed in importance both professional reviews and advertisements is of interest. This ascension in importance likely justifies the management investment required to manage the medium as the time spent responding to negative comments found on CGM sites should be returned in the form of increased bookings from reassured potential guests.
Further, CGM reviews should be useful to hospitality marketers in identifying those aspects of their service product of most importance to their guests. Postings by previously delighted guests who feel motivated to share their positive commentary with others via CGM will raise the expectations of future guests. Taking a page from Importance Performance Analysis [IPA] modeling, from positive postings management can learn those aspects of their service product that most delighted guests. These would fall in the ‘Keep up the Good Work” quadrant of the model, reflecting high importance (otherwise they would not be discussed in the review) and high performance attributes. Be aware that future guests will expect continued excellence in these areas. For negative comments, again following the IPA model, management should consider these ‘Focus Here’ (high importance, low performance) priorities. Addressing these will improve future guests’ experiences…and perhaps delight those who have come to the property with concern they might face the same issues.
12 Supporting the findings that CGM can enhance customer service were comments made by several hoteliers with whom this study was discussed. These hoteliers noted how critically important it was for them to avoid negative reviews; and how fear of negative electronic word-of-mouth has, they believe, resulted in their having raised the quality standards of their properties. Further, they noted, an effect of online reviews has been increased flexibility in the enforcement of their own policies. With guests holding the power that comes from the threat of a negative review, they indicated they were far more willing than in the past to bend to guest demands.
RESEARCH LIMITATIONS AND FUTURE STUDY
There are limitations to this study that future researchers should consider. In the opinion of the authors, none of these are of such significance that they invalidate the reported findings.
- The convenience sample was not a reflection of the broader USA population. It had a disproportionate share of females and was more highly educated than are Americans in general. However, as the experiment was designed to evaluate participant attitudes rather than to provide point and interval estimates of population parameters (Calder, Phillips, and Tybout, 1981), the sample was deemed reasonable for the current study.
- It was elected to use three star hotels for the study, allowing the greatest range of variation above and below the initial ratings to evaluate impact of the scenarios. The research should, however, be replicated for other class properties, as users may have different responses to online postings for these properties.
- Sundaram and Webster (1999) noted that the evaluation of familiar brands is less susceptible to influence by the opinions of other consumers. Vermeulen and Seegers (2009:126) confirmed this for hotels, noting the “persuasive effect of online reviews [to be] stronger in lesser-known hotels.” The current study intentionally avoided issues
13 related to brand familiarity by using fictitious non-branded properties. Further study should consider incorporating branded properties to determine if this would affect the impact of consumer and managerial responses to CGM postings.
- Finally, it is recommended that the research be replicated for other segments of the industry. Do restaurant patrons similarly react to guest and management responses? How about attractions, or even destinations? Future research using other industry segments will further enhance our learning of this important topic.
CONCLUSION As noted in the introduction, multiple authors (e.g. Vermeulen & Seegers (2009), Ye, Law & Gu (2009), Yoo & Gretzel (2008)), have reported that positive CGM reviews can lead to increased hotel bookings. The current findings support this assertion, extending the prior work by considering the impact of customer rebuttals and management responses to a negative comment in a hotel review. The addition of these commentaries, this experiment has demonstrated, has the power to improve a potential guest’s attitude towards a hotel being considered for one’s next travel experience, thus likely improving the hotel’s future performance.
Litvin, Goldsmith and Pan (2008) posit that electronic-word-of-mouth via CGM provides an opportunity rather than a threat to the hospitality industry. The current study confirms that the investment required to ‘manage’ a hotel’s review sites represents such an opportunity; and that the time and effort doing so likely will be rewarded.
Technology is constantly changing, and it is important for hospitality businesses to adapt to these changes. Electronic word-of-mouth via CGM provides hospitality industry providers a higher than ever before level of awareness of their guests’ views regarding their properties. It is up to management to harness this knowledge and to steer consumer attitudes. The message herein: hospitality managers must make CGM work as a positive force. Nothing is more important than providing a high quality product in the first place.
14 Delight guests and today they can say positive things about their experience to an audience many times greater than has been available to the consumer of the past. Be proactive to encourage these positive reviews. But also be responsive to negative reviews to counteract the impact these can have on potential guests.
CGM is not going to go away, and it is likely the medium will play an even greater role in the future traveler’s decision making process. Management should embrace CGM and make it work in their favor to remain competitive in an increasingly virtual world.
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19 Table 1 Experiment Participant Demographics Percentage of Participants Sex (n=258) Female Male Age group (n=225) 18-35 36-55 56+ Mean Age=45
71 29
28 48 25
Education (n=255) High School Some College Undergraduate Degree Post-graduate Degree
4 22 41 33
Profession (n=216) Student Homemaker Blue Collar White Collar Other
10 3 13 61 12
Previous user of online review sites (n=259) Yes No
80 20
Reasons for previously using online review sites (n=255) When Planning a Trip Just for Fun Both N/A
68 2 9 21
20 Table 2 Experiment Results Pre-test rating Hotel Plaza (no treatment) Vista (customer rebuttal) Summit (mgmt rebuttal)
9.7 8.5 9.2
PostPercent experiment change rating 9.9 unchanged 6.0 + 29% 7.8 + 15%
T-score
p value
0.493 -8.528 -3.685
0.622 0.000 * 0.000 *
- The lower the score the more favorable the rating. The potential response range was three to fifteen, based upon three questions, each with a five-point response option. * Significant at p
