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CONFERENCE PROCEEDINGS
14th Toulon-Verona Conference “Organizational Excellence in Services”
University of Alicante - University of Oviedo (Spain) – September 1-3, 2011
pp. 799-814 – ISBN: 978 88904327-1-2
THE IMPACT OF HOTEL REVIEWS POSTED BY GUESTS ON
CUSTOMERS’ PURCHASE PROCESS AND EXPECTATIONS
Aurelio G. Mauri, Università IULM, Milano, Italy , [email protected]
Roberta Minazzi, Ph.D., Università dell’Insubria, Como, [email protected]
ABSTRACT
From the first article published on the topic of electronic word-of-mouth – eWOM (Stauss,
1997) research has rapidly increased, underlining the importance of this phenomenon both in
academic and business contexts. The purchasing behaviour of the customer has increasingly
changed with the development of new technologies. Therefore, what had traditionally been
defined as word-of-mouth (WOM) (Arndt, 1967; Koenig, 1985) needed to be reconsidered
and studied in light of recent changes (Buttle, 1998; Breazeale, 2009). Electronic WOM
through online reviews on specific websites, company websites, blogs and communities
influences various steps of the consumer decision-making and purchasing processes
(Schindler and Bickart, 2005) and his expectations of the service.
The objective of the paper is to study the impact that customer feedback/reviews posted on
“non-transactional” websites have on the consumer decision-making process and on tourist
expectations in the hospitality industry, which is particularly affected by this new trend. Many
travel services are now bought on the net using electronic distribution systems: flights, hotel
stays, car rentals, etc. (Nielsen, 2010; PhoCusWright, 2010). Online reviews play a key role
in purchasing travel services (Nielsen, 2010) and “non-transactional” website traffic
increased by 4% from 2007 to 2009 despite a decrease for transactional websites (OTA,
company websites, etc.) (PhoCusWright, 2009). Therefore, hotel companies should
comprehend the way customer feedback influences other consumers’ decisions and
expectations in order to develop specific marketing strategies that also consider the synergy
among social media and the development of mobile technologies.
Keywords: electronic word-of-mouth (eWOM), word-of-mouse, hotel reviews, purchase
behaviour, expectations
INTRODUCTION
The Internet is now the predominant means of travel shopping in European countries and has
changed the way tourism information is distributed (Buhalis, Law, 2008; Law et al., 2008).
70% of French travellers and nearly 80% of German and U.K. travellers typically use the
Internet when shopping for travel, at least as a source of information. The second source of
information is personal recommendations from family and friends, which is true of 40% of
German and U.K. tourists and less than 40% of French travellers (PhoCusWright, 2010).
More recently, tourists have been able to benefit from a new and convenient way of gathering
information directly when they arrive at their destinations thanks to the development of
mobile technologies (Buhalis, Law, 2008).
The advent of the Internet has brought about a word-of-mouth revolution. In fact,
individuals can make their thoughts and opinions easily accessible to the global community
of Internet users (Dellarocas, 2003). We can consider eWOM a form of communication that
provides a mechanism to shift power from companies to consumers (Hennig-Thurau et al.,
2004).
In this context, online reviews play a key role in purchasing travel services (Nielsen,
2010) and ―
non-transactional‖ website traffic has increased by 4% from 2007 to 2009 despite
a decrease for transactional websites (Online Travel Agencies-OTA, company websites, etc.)
(PhoCusWright, 2010).
A study conducted by Gretzel (2007) on a sample of Tripadvisor users confirms the
importance of online reviews during the step of travel planning especially in deciding ―
where
to stay‖ (77.9%). Virtual communities (TripAdvisor, VirtualTourist, LonelyPlanet) are the
most-used travel websites (92.3%), especially for gathering information, evaluating
alternatives, avoiding unenjoyable places and providing ideas.
Online travel sales, especially for Hotels, account for only 7% in Europe while OTAs
are the most-used means of travel booking (PhoCusWright, 2010).
Key segments in online travel are:
 Online Travel Agencies (OTAs);
 suppliers’ direct websites;
 tour operators;
 online corporate booking tools;
 non transactional/media travel sites;
 emerging media and channels (for instance smart phones and social network such as
Facebook and Twitter).
These last two operators aim to facilitate and enrich online travel planning, enabling the
customer to share information and experiences with other travellers. Actually, nontransactional websites can have two different goals: reviewing and trip planning (such as
TripAdvisor and Lonely Planet) and Metasearch (such as Kayak, cheapflights) that compare
the offers of different OTAs (Buhalis, O’Connors, 2005). On the contrary, emerging media
and channels like social networks (Facebook, Twitter, etc.) are more oriented towards
relationships among travellers even if more and more possibilities are given to the companies
to directly create personal relationship with the customer (Pan et al., 2007; Jansen et al., 2009;
Xiang, Gretzel, 2010). In this group of operators, mobile applications that allow customers to
facilitate almost all the steps of the purchase process are the new frontier (I Phone, etc.)
(Shankar, Balasubramanian, 2009; Sultan et al., 2009).
This paper focuses on ―
non-transactional‖ websites in the hospitality industry and aims
to evaluate the influence of customer reviews on his purchase intentions and expectations.
Finally, the study intends to verify whether the power of negative consumer comments can be
minimized through appropriate company response. The issue is investigated by presenting an
experimental study on the impact of online hotel reviews on consumer decision-making and
expectations.
1.
THE EVOLUTION OF THE CONCEPT OF WORD-OF-MOUTH
1.1. Word-of-mouth vs. electronic word-of-mouth
The development of new technologies and the trends identified in the previous
paragraph pointed out the need to reconsider the concept of word-of-mouth (WOM), as
traditionally intended, in light of recent changes (Buttle, 1998; Breazeale, 2009).
Arndt (1967) and Koenig (1985) define WOM as ―
an oral, person-to-person
communication between a receiver and a communicator whom the receiver perceives as noncommercial, regarding a brand, product or service‖. WOM involves the exchange of
ephemeral oral or spoken messages between a contiguous source and a recipient who
communicate directly in real life. Consumers are not thought to create, revise and record prewritten conversational exchanges about products and services. This kind of communication
vanishes as soon as it is uttered, for it occurs in a spontaneous manner and then disappears
(Buttle, 1998).
Stern (1994) underlines that WOM is different from advertising because it is not
influenced and paid for by the company. This increases the perception of credibility by the
customers (Bateson, Hoffman, 1999; Ogden, 2001). Villanueva et al. 2008 and Trusov et al.
2009 found that customers acquired through eWOM add more long-term value to the firm
than customers acquired through traditional marketing channels.
By analysing these definitions, we can identify the main differences between the
traditional concept of WOM and the new idea of eWOM. First of all, eWOM is not
necessarily direct or oral because customers write their impressions on the net and they do not
vanish immediately; on the contrary, other consumers can consult these reviews even after a
long period of time (Buttle, 1998; Breazeale, 2008). In the electronic environment, the
opinions that consumers post on the Web are seen by millions, are available for long periods
of time, and may be encountered by purchasers at precisely the time they are electronically
searching for information about a particular product or service (Ward, Ostrom, 2002).
Secondly, eWOM communication is not limited to brands, products or services but can be
related to an organization, destination, etc. (Buttle, 1998). Thirdly, although eWOM remains a
source of information from the company and different from advertising, it is sometimes
incentivized and rewarded (Buttle, 1998). This can create some problems with the credibility
of the message, as the source of the message is unknown. In fact, in eWOM communication
the information comes from individuals who have little or no prior relationship with the
seeker (Xia, Bechwati, 2008; Schindler, Bickart, 2005). It is difficult for the consumer to
determine the credibility of the message when it comes from total strangers (Chatterjee, 2001)
with diverse backgrounds (Litvin et al., 2008). For this reason, sometimes online travel
intermediaries require reviewers to provide personal identifying information (PII) (e.g., name,
state of residence, gender, and date of visit/stay) (Xie et al., 2010). This is the case
Tripadvisor, for example.
According to Hennig-Thurau et al. (2004) eWOM is ―
...any positive or negative
statement made by potential, actual, or former customers about a product or company, which
is made available to a multitude of people and institutions via the Internet‖ (Hennig-Thurau et
al., 2004).
Online WOM messages can be shared through posted reviews (consumer opinions on
apposite websites), mailbags (customer opinions on the website of the seller), discussion
forums, electronic mailing lists (consumer opinions sent by e-mail), personal e-mail, chat
rooms (real time conversation on a topic) and instant messaging (one-to-one real conversation
on the internet). Schindler and Bickart (2005) conducted a study on a sample of frequent
internet shoppers and found that the most frequently-used source of online WOM is consumer
reviews and the main reasons are: to gather information about brands or products by
consulting the experience of a lot of people and to support or confirm a previously-made
decision. Sometimes people search for information just for fun, without any real intention to
purchase but this action, even if passive, can influence future purchase decisions.
However, customer comments present some biased information. Firstly, people who
post a comment on the net are generally extremely satisfied or extremely dissatisfied
(Anderson, 1998; Hu et al., 2007; Litvin et al. 2008). Positive reviews refers to favourable
experiences and a consequent recommendation of the product to other customers, whereas
negative feedback refers to unfavourable experiences and are meant to dissuade others from
buying that product. The customer can have an attitude of aggressive complaint or a more
moderate attitude trying to alert other consumers to the risk of the product (Cheng et al.,
2006).
Secondly, it is also possible to identify purchasing bias because only consumers with a
favourable disposition towards a product purchase the product and have the opportunity to
write a product review (Hu et al., 2007).
Thirdly, those who write a comment about a purchased product are influenced by
features other than objective product quality, leading to a reporting bias in these reviews. By
the way, the listener is generally conscious of this bias and filters the information (Banerjee
and Fudenberg, 2004; Hu et al., 2006).
Finally, it is sometimes possible to find fake positive or negative reviews posted by the
company or by the competitors trying, in the first case, to improve the company’s reputation,
and, in the second, to damage the reputation of a competitor (Dellarocas, 2003).
Given the decontextualization, anonymity and bias, eWOM may appear nebulous to
consumers. As a result, consumers’ interpretations of eWOM and subsequent purchase
intention may be substantively affected by their pre-existing disposition toward the service
provider (Xie et al. 2010).
1.2. Credibility of online customer reviews
WOM can be analysed considering various dimensions (Mauri, 2002):
 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).
In this study we focus especially on valence and credibility of online comments.
Credibility of eWOM is influenced by informative aspects and normative cues
(recommendation consistency, recommendation rating) that may be able to supplement the
informational cues (Cheung, 2009).
Argument strength concerns the quality of the information received. It is the extent to
which the message receiver views the argument as convincing or valid in supporting its
position. For example, the presence of details and personal identifying information (PII) of
the reviewers (Xie et al., 2010) describing a first-hand experience and the consensus of other
reviewers are generally cues of the message's validity (Schindler, Bickart, 2005; Park et al.
2007). On the contrary, a lack of negative comments and undetailed or very general messages
are considered untrustworthy (Schindler, Bickart, 2005; Schlosser, 2005; Doh et al., 2009).
Recommendation framing refers to the valence of the eWOM (positively framed or
negatively framed) while recommendation sidedness refers to the content of the message that
can contain only one-sided information (positive or negative) or two-sided information (both
positive and negative). Two-sided information is generally considered more credible because
of the consumer each product has positive and negative features. Therefore two-sided
descriptions are perceived as more detailed information influencing the argument strength
(Cheung, 2009).
Another key factor is source credibility, which refers to the reputation of the reviewer
that is sometimes conferred by the administrator of the website and other times with specific
and formal ranking on the basis of the message’s helpfulness (Henning-Thurau, 2004).
Due to the bias reported in the previous paragraph, the customer tries to find reviews
consistent with his or her prior knowledge or expectations, increasing his perception of review
credibility (Xie et al., 2010). In fact, Xia and Bechwati (2008) found that the influence of the
comment depends on the cognitive personalization initiated by the reader. If he perceives the
situation as familiar, he processes the information in a self-referential manner and the review
becomes more credible, valid and trustworthy.
Another important aspect that influences the credibility of an online consumer opinion
is the website where it is posted. Feedback on corporate websites is generally considered less
credible that those on non-transactional websites (such as Tripadvisor, Zoovers, etc.) (Park et
al., 2007). With this in mind, some companies prefer to attach a link to these websites despite
creating a guest comment page.
The credibility of the review is therefore a key factor that leads the consumer to
consider or disregard the message during the purchase decision process.
2.
CONCEPTUAL FRAMEWORK
2.1. The impact of online customer reviews on purchase intentions
Academic studies on the topic of online word-of-mouth have pointed out the impact of
consumer reviews on the purchase intentions and decisions of the customers. Online reviews
on specific websites, company websites, blogs and communities influence various steps of the
consumer decision-making and purchasing processes (Schindler, Bickart, 2005; Park et al.,
2005; Buhalis, Law, 2008).
Several recent studies on the topic of eWOM agree on the deep impact of online
reviews on customer purchase intentions. An extant stream of work has looked at the
economic impact of reviews on companies’ financial performances by means of numeric
variables representing the valence (positive or negative) and volume of reviews. This
hypothesis received strong support in prior empirical studies (Chevalier, Mayzlin 2006;
Dellarocas, 2003; Dellarocas et al. 2006; Forman et al. 2008; Villanueva et al., 2008; Luo,
2009; Godes, Mayzlin 2009).
The effect of eWOM and online travel reviews on consumer behaviour has also been
studied in the travel and tourism industry – especially with reference to information searching,
holiday planning and purchase decisions (Gretzel, Yoo, 2008; Gretzel et al., 2007; Litvin, et
al., 2008; O´Connor, 2008; Papathanassis, Knolle, 2010; Sidali et al., 2009; Vermeulen,
Seegers, 2009; Ye et al., 2009).
Exhibit 1. The impact of online WOM on purchase decision making
Source: Schindler R., Bickart B. (2005), Published 'Word of Mouth': Referable, Consumer-Generated
Information on the Internet, in C. Hauvgedt, K. Machleit, R. Yalch (Eds.), Online Consumer Psychology:
Understanding and Influencing Behavior in the Virtual World, Lawrence Erlbaum Associates. (pp. 35-61).
The valence (positive or negative) of the message is one of the most considered
variables. Sen and Lerman (2007) found that the valence of the review (positive or negative)
influenced consumer behaviour but in different ways depending on the kind of product
(hedonic versun utilitarian). Also, the balance of positive and negative comments can be a
factor considered by the customer. In fact, if the consumer perceives a low level of consensus
he is believed to think that the authors of negative reviews are unable to use or evaluate the
product. On the contrary, in the case of more consensus on the negative side the customer will
develop negative inferences towards the product and the brand (Laczniak et al., 2001).
In particular, various studies concentrate on the potentially more influential effect of
negative than positive WOM because of the detrimental impact on businesses. A study of
Chatterjee (2001) indicates that negative consumer reviews have negative effects on perceived
company reliability and purchase intentions. The effect could be more negative in the case of
a company unfamiliar to the consumer. Other authors have investigated the behaviour of the
dissatisfied customer and found that he is more likely to express feelings to other people
through negative WOM (Richins, 1983; Morris, 1988; Hart and Heskett, 1990; Tax, Brown,
& Chandrashekaren, 1998).
Bambauer-Sachse and Mangold (2011) confirm with their research that negative online
product reviews have detrimental effects on consumer-based brand equity leading to a
significant brand equity dilution, even if the brand is familiar to the customer.
On the contrary, other studies affirm that the influence of negative WOM is not so
different from that of positive comments (Ricci, Wietsma, 2006). Vermeule and Seegers
(2008) found that both positive and negative reviews increase consumer awareness of hotel
existence but, if the comments are negative, they lower consumer opinions. Neverthless, the
hotel awareness generated compensates the effect of negative comments, especially if the
quantity is low (Vermeulen, Seegers, 2008).
Other streams of research focus on other variables that influence the structural process
of how online consumer reviews influence purchase decisions. Park and Lee (2009)
investigate and examine the role of national culture on these relationships by comparing U.S.
and Korean consumers' behaviours. According to Xie et al. (2010) the presence of PII
increases the credibility and subsequently purchase intention of the customer in the hospitality
industry.
Some other studies, in contrast to the ones previously cited, found that customer
comments on the web are predictors of sales but do not influence them (Chen et al., 2004;
Duan et al., 2008).
Another important point is the nature of the product. According to some scholars, WOM
recommendations play a significant role in consumers’ decision-making processes, especially
when dealing with services or intangible products rather than with tangible ones (Murray,
Schlacter, 1990; Gremler, 1994). Intangible services are particularly complex and difficult to
evaluate prior to purchase and the perception of risk is higher because its quality is often
unknown before consumption (Baccarani, Golinelli, 1992; Rosen, 2000; Dye, 2000; Zeithaml
et al., 2006). Moreover, in the hospitality industry, WOM recommendations are even more
influential due to the nature of inseparability between service production and consumption
and the importance of the customer experience (Lindberg-Repo, 2001; Grönroos, 1999).
The first hypothesis of the present research is:
H1: The hotel booking intention of the customer is different depending on the valence of the
review posted on “non-transactional” travel websites: it increases in the case of a prevalence
of positive comments and decreases in the case of negative comments.
2.2. The impact of review valence on customers’ expectations
The scholars of services marketing consider WOM as an antecedent of customer
expectations. Grönroos (1982) believes that 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 and 1993; Zeithaml et al., 1985). Zeithaml
et al. (1993) propose a model that conceptualizes the nature and determinants of customer
expectations of services: among others, consumer experience and enduring service intensifiers
influence desired service especially in the case of derived service expectations that are driven
by other parties. During the step of information research customers gather information about
the service from various known (WOM) and generally unknown (EWOM) sources trying to
determine what to expect by a specific service. During the communication process customers
share experiences that can have a positive or a negative valence (Mauri, 2002).
H2: The level of expectation of the customer differs depending on the valence of the review
posted on “non-transactional” travel websites: it increases in the case of prevalence of
positive comments and decrease in the case of negative comments.
2.3. The impact of hotel reply on purchase intentions and customer expectations
How can a Hotel try to minimize the impact on negative comments on booking
intentions and on expectations?
Recent studies suggest that the widespread use of eWOM and online hotel reviews can
be an opportunity rather than a threat for hotel managers and operators (Litvin et al., 2008).
Companies that understand the importance of WOM are taking advantage of online consumer
reviews as a new marketing tool (Dellarocas 2003), posting product information and chatting
on online forums. Godes and Mayzling (2009) use the term ―
exogenous WOM‖ to describe
the proactive actions of companies that induce their consumers to spread the word about their
products online (Godes and Mayzlin 2004; Godes and Mayzlin 2009). Viral marketing
campaigns are considered more and more important in combination with offline marketing
strategies (van der Lans et al., 2010). Some firms even strategically manipulate online reviews
in an effort to influence consumers’ purchase decisions (Dellarocas 2006).
Chen and Xie (2008) conducted a study to try to understand the way a company should
interact with consumer reviews to increase profits, trying to control online word-of-mouth.
They found that the response of the company should change according to the type of product
and the kind of information. Other studies confirm that the company should strategically
respond to online consumer reviews (Chen, Xie 2005, Dellarocas 2006; Zhu and Zhang, 2010;
Xie et al., 2010). However, no previous academic studies have yet explored the effect of
company response to customers’ reviews on booking intentions and expectations of the
customer.
We also have to consider two kinds of problems that interfere with hotel operator
response activity. On the one hand, the hotel operators are not completely conscious of the
effect of online word-of-mouth on the customer and, consequently, they undervalue this
phenomenon. Moreover, hotel managers sometimes do not have appropriate IT knowledge
due to the customer-oriented approach of the service sector. IT has always been seen as an
instrument to reach customers but rarely is it integrated into the company’s business strategy
(Law, Jogaratnam, 2005; Law et al. 2008). On the other hand, a conflictual relationship
between hotel companies and websites that publish travel reviews complicates the situation.
Recently, replying to negative comments on the web has become easier for the hotel
companies thanks to an improvement in the business relationship and cooperation among
offline and online travel operators. Speaking with a few hotel operator we find out that they
consider the possibility to reply to customers an important opportunity to increase customer
perceptions of service quality and booking intentions. However, hotel managers’ reply can be
considered not credible because not independent but related to the company (Buttle, 1998).
The consumer could perceive that message very similar to advertising (Stern, 1994) also
because the messages generally are not personalized.
Therefore, it is interesting to address the following research question:
RQ1: the hotel responses to customer reviews posted on “non-transactional” travel websites
could have a positive and useful effect on customer booking intention and on his
expectations?
3.
RESEARCH METHODOLOGY
An experimental study was conducted to test the hypotheses and the research question
in June 2011. To eliminate the possibility of bias, three scenarios were built around an
unbranded hotel. In fact, brand familiarity can play an important moderating role in the
consumer’s perception of comments: familiar hotel brands could be more resilient to review
effects than unfamiliar brands (Chatterjee, 2001; Vermeulen and Seegers, 2008).
Those involved in the survey were asked to imagine searching for a hotel for a weeklong holiday in an unknown location without any previous experience. This decision was
meant to eliminate possible bias from the customers’ previous personal experiences. After the
presentation of the context, the participant was asked to read other customers’ reviews of a
hypothetical chosen hotel.
The hotel reviews presented in the three scenarios were created by studying a few
comments posted by customers on the main websites used by tourists (such as Tripadvisor).
In fact, the structure was very similar to other existing websites but we changed the main
recognition seals to avoid any kind of reference to well-known sites and therefore the
influence of site brand image. For the same reason, other information about the hotel was also
excluded from the survey (price, room amenities and services). The review consisted of a
synthetic title, the ranking, the date of the review and the comment of the customer. They
were presented in order of date published for the period January 2011-until now (period of
research).
The creation of three different questionnaires aimed to verify the previously-stated
hypotheses. To do that, the first scenario presented a prevalence of positive reviews (7 vs. 3),
the second scenario presented the opposite situation, that is, a prevalence of negative
comments (7 vs. 3), the third scenario presented the previous context (prevalence of negative
comments) but, in this case, the reply of the hotel manager was reported.
The order of positive and negative reviews was counterbalanced to control any possible
order effect (Carlson et al., 2006). To increase comment credibility, we used two-sided
information (Henning-Thurau, 2004).
At the end of the comments, participants were asked to answer a few questions to try to
understand the soundness of the hypothesis (H1 and H2) and to answer the research question
(RQ1). Purchase intention was evaluated on a 7-point scale (1-most likely not to buy, 7-most
likely to buy) as was the level of expectation (1 for low expectations, 7 for high expectations)
Respondents Profile
360 online questionnaires were sent to undergraduate and graduate italian students with a
result of 102 respondents (response rate of 28.9%). The choice was considered appropriate
from the age point of view because, according to Italian statistics, more than 30% of people
that buy online are between the ages of 25 and 34 (Istat, 2009). Participants were randomly
assigned to one of three groups corresponding to three different scenarios.
Respondents are mainly women (73.5%) between the ages of 18 and 25 (82.4%). This
composition is also the main limit of the study, that is a pilot study and need to be extended.
Table 1 Respondents features: age and gender
age
18-25
Count
scenario 1 % within scenario 1
% of Total
Count
scenario 2 % within scenario 2
% of Total
Count
scenario 3 % within scenario 3
% of Total
Count
Total
% of Total
4.
26-35
21
63,6
20,6
30
96,8
29,4
33
86,8
32,4
84
82,4
6
18,2
5,9
1
3,2
1,0
3
7,9
2,9
10
9,8
> 36
Total
6
18,2
5,9
0
0,0
0,0
2
5,3
2,0
8
7,8
33
100,0
32,4
31
100,0
30,4
38
100,0
37,3
102
100,0
man
7
21,2
6,9
9
29,0
8,8
11
28,9
10,8
27
26,5
gender
woman
26
78,8
25,5
22
71,0
21,6
27
71,1
26,5
75
73,5
Total
33
100,0
32,4
31
100,0
30,4
38
100,0
37,3
102
100,0
FINDINGS
A first result to be analyzed is that more than 76% of respondents consult comments of other
customers before booking a hotel. This confirms the importance of online customer feedbacks
stated in the previous part of the paper.
The first hypothesis (H1) claims that there is a positive correlation between hotel booking
intention of the customer and valence of the review posted on ―
non-transactional‖ travel
websites. In particular, it increases in the case of a prevalence of positive comments and
decreases in the case of negative comments. Comparing the mean of each scenario (table 2),
the average score of booking intention rises from 4.10 to 4.52 shifting the scenario from 2
(prevalence negative reviews) to 1 (prevalence of positive reviews). The correlation, by
means of Spearman’s rank correlation coefficient, supports H1 (table 3) and demonstrates a
positive (rs= 0.246) and significant (p<0.05) correlation between booking intention and
valence of the message.
Table 2 Booking Intention and level of expectations according to each scenario
Booking
intention
Scenarios
Scenario 1
Prevalence of positive
reviews
Mean
Scenario 2
Prevalence of negative
reviews
Mean
Scenario 3
Prevalence of negative
reviews with hotel reply
Mean
Std. Deviation
Std. Deviation
Std. Deviation
Mean
Total
Std. Deviation
Level of
expectations
4.52
4.58
1.121
1.001
4.10
4.39
0.900
1.116
3.82
4.34
1.205
1.214
4.13
4.43
1.125
1.113
The second hypothesis (H2) claims that there is a positive correlation between the level of
customer expectations and valence of the review posted on ―
non-transactional‖ travel
websites. Table 2 shows, an average score (M=4.58) higher in the case of prevalence of
positive comments than in the case of negative comments (M=4.39). However, we cannot
statistically demonstrate a relationship between reviews’ valence and level of customer
expectations because, as shown in table 3, the correlation is not significant (p>0.1).
Research questions (RQ1) investigated whether the hotel responses to customer reviews
posted on ―
non-transactional‖ travel websites could have a positive and useful effect on
customer booking intention and on his expectations. Table 2 shows that in the case of hotel
managers’ responses the average score descreases (M=3.82). The correlation by means of
Spearman’s rank correlation coefficient demonstrates a positive (rs= 0.209) and significant
(p<0.05) correlation between booking intention and the presence of hotel responses (table 4).
This result supports the position that considers hotel responses as less credible because not
independent from the organization. However, also in this case we cannot demonstrate a
relationship between reviews’ response and level of customer expectations because, as shown
in table 4, the correlation is not significant (p>0.1).
Table 3 Correlation between review valence (positive vs. negative) and booking intention and level of
expectations (H1 and H2)
Dimensions
rs
Sig.
Booking intention
0,246
0,014
Level of expectations
0,101
0,313
Table 4 Correlation between hotel response presence and booking intention and level of expectations
(RQ1)
Dimensions
5.
rs
Sig.
Booking intention
-0,209
0,038
Level of expectations
- 0,062
0,534
DISCUSSION
As expected, the results obtained through the analysis support the first hypothesis of the study
that consider valence of reviews posted on ―
non-transactional‖ travel websites and hotel
booking intention positively related, confirming the persuasive impact that positive comments
can have on customer decision making process (Sen, Lerman, 2007; Sparks, Browning,
2011).
The most interesting research point of the study was to verify the effect on hotels’ reply to
negative comments on booking intention and expectations. Results show that including the
hotel responses to customer reviews has a negative effect on customer booking intention. This
confirms the approach that considers the hotel’s reply more similar to advertising and
therefore perceived by the customer as less credible because not independent from the
organization. Hotel operators should try to reduce negative WOM and stimulate positive
reviews through personalized activities that increase customer satisfaction, for example:
improving the level of service delivered to the customer by trying to reduce the volume of
negative comments; improving the service recovery when the customer is already at the hotel,
stimulating complaints; conducting customer satisfaction surveys and personal interviews and
developing guest comment areas on the websites when the customer has already gone home.
The effect of online service recovery policies, by means of hotels’ reply to negative comments
on ―
non transactional‖ websites, have not the same effect of personal complaint handling. The
message could not be read by the customer who posted the review and other customers
perceive it as commercial communication. The hotel company should find other ways to
create an interaction with customers on the web, using social media and stimulating positive
online and offline word-of-mouth.
6.
CONCLUSIONS
The paper demonstrates that booking intentions in the hospitality industry are
influenced by valence (positive or negative) of online reviews posted on travel ―
non
transactional‖ websites, providing further theoretical and practical knowledge on this topic. In
particular, online travel reviews is confirmed to be an important source of information which
influences customer decision making process and booking intentions.
The presence of hotel managers’ reply to customer reviews is not considered a key
factor by the customer. On the contrary, it has a negative impact on customer booking
intention. The source of information in this case is probably seen as not spontaneous and not
independent from the organization.
These results, in light of managerial implications described in the previous paragraph,
can support hotel operators in defining integrated communications strategies based on a
synergic use of new media and technologies, without forgetting the importance of personal
relationships and service recovery when the customer is already at the hotel. In fact, service
quality evaluation and customer satisfaction remains key factors stimulating positive online
customer reviews.
7.
LIMITATIONS AND FUTURE RESEARCH
The present paper is based on an explanatory study that presents some limitations. First
of all, it is based on a convenience sample and respondents are mainly concentrated in a
specific age and gender group. It is necessary for the future to continue the research on a
wider sample. This could be helpful also to verify the relationship between review valence
and customer expectations resulted not significant in this study. Secondly, the experimental
approach limits the investigation to selected variables. In fact, many other variables can
influence booking intentions and customer expectations such as personal interests of the
customer. Thirdly, even if credibility standards were respected, creating the reviews content is
a limitation to what information was presented in the scenarios.
Future research could explore the relationship between hotel reply to online customer
reviews and company image and reputation. Moreover, it could be interesting to verify the
actual booking behaviour of the consumer, not only the intention in the pre-purchase step, and
the influence of social media on eWOM.
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