Tesi di laurea in Economia del turismo in inglese, in International Marketing in Tourism, Valentina Paci

Jalilvand, Samiei, Dini and Manzari (2012) focused their analysis on the mutual

relationship between electronic word of mouth (eWOM), destination image, tourist attitude

toward the destination and travel intention in the tourism context. The Authors hypothesized

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that i) electronic word of mouth has a positive impact on destination image, on tourist attitude

toward the destination and on travel intentions; ii) destination image positively influence

travel intentions and attitude toward the destination; iii) tourist attitude toward the destination

has a positive impact on travel intention. The methodology used to conduct the analysis was

the collection of 264 questionnaires to international visitors in Isfahan, Iran. The study tested

all the six hypotheses and concluded that all were supported. Results suggested that eWOM,

destination image and attitude toward the destination are three important criteria in

influencing travel intention, while eWOM is also an antecedent of destination image and

attitude toward the destination. This was the first paper analyzing the interrelationship

between these four constructs to study the tourism online environment. One limitation of the

analysis includes the fact that the sample may not be representative of the whole international

tourists.

Boo and Busser (2017) investigates online reviews on TripAdvisor from meeting

planners to value their hotel experiences and analyze the elements that comprise their review.

The authors gathered 734 meeting planners’ reviews across 173 hotels that had comments and

ratings in the period 2007-2015, retaining 696 reviews for the subsequent analysis. Thus, a

twofold content analysis method was adopted, using first the software Leximancer to examine

the conceptual structure of the review contents; and then a manual analysis to classify them.

Meeting planners’ online reviews were assessed in order to check for the presence and

frequency of concepts, as well as how these elements were interrelated. The key concepts

found in the reviews were eight: staff, meeting, hotel, property, work, location, recommend

and amenities (in order of declining occurrence). The results of the subsequent manual

content analysis answered to the four research questions concerning: i) the text features

emerged in meeting planners’ reviews; ii) the extent of behavioral intentions; iii) the relation

of the quantitative features in online reviews and with behavioral intentions; iv) the elements

related to positive or negative reviews. The first answer was that the majority of their reviews

are related to personal stories during the meeting. The second point was that recommendation

and return intention are affected by message tone and valence. The third question concluded

that the lengthier the review is, the lower the possibility of recommendation; which was, in

contrary, positively related with review score. The fourth question was able to conclude what

the major areas of satisfaction are (meeting and staff) and of dissatisfaction (meeting, staff

and hotel). This analysis was helpful to differentiate the analysis of meeting planners’ reviews,

to that of general travelers. 23

Zhao, Wang, Guo and Law (2015) focused on the impact of online reviews on the hotel

booking intentions of travelers. In detail, they considered six factors related to online reviews

content, i.e. usefulness, reviewer expertise, review timeliness, review volume, review valence

and review comprehensiveness, to test their positive relationship with online booking

intention. Specifically, they hypothesized that the helpfulness of a review has a positive

impact on booking intentions; reviewer expertise, meaning the capability to provide correct

information, positively influences booking intentions; and that current and up-to-date

(timeliness) reviews positively affect hotel online bookings. Moreover, the Authors

hypothesized that a high volume of reviews has a positive impact on booking intentions; that

positive reviews have a positive influence on intentions, (while, conversely, negative reviews

have a negative impact); and that comprehensiveness of the review has a positive effect on

online hotel booking intentions. The Authors generated an initial list of measurement items

for each of the considered review features. Then, a pretest with 109 undergraduate students in

mainland China was used to test the reliability of 29 proposed items. Based on the

measurement scales derived from the pretest, a questionnaire was developed and administered

to 269 participants. The results showed that all the hypotheses have been supported, except

for the positive influence of positive online reviews on hotel booking; revealing that all the

considered features (review usefulness, reviewer expertise, review timeliness, review volume

and review comprehensiveness) have a significant positive relationship with booking

intentions; while negative reviews have a negative impact.

Sreejesh and Anusree (2016) investigated the role of webcare (i.e. the act of replying to

customers’ complaints and give explanations for service failures) as a service failure recovery

strategy on customers’ hotel booking intentions, considering different levels of observed

severity (i.e. the extent of loss experienced after the service failure) and review agreement

(i.e. the number of helpfulness votes). The Authors proposed a scenario in which a potential

customer found online some negative reviews about the service failure of a hotel, aiming to

investigate how this can influence the customer’s booking intentions, manipulating webcare

activity, severity and review agreement. The Authors hypothesized that: i) the higher the

severity of the negative review, the lower the intention to book; ii) a huge number of reviews

with a high level of agreement decreases booking intentions; iii) the effect of a negative

review with a high level of involvement is mitigated by the presence of webcare; and iv)

webcare increases trust toward service provider, therefore mitigating the effect of a severe

negative review with a high level of agreement. The Authors conducted an experiment with

252 undergraduate students from a large Indian University, manipulating the levels of the

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investigated variables: severity of the review (high or low), level of agreement (high or low)

and webcare (presence or absence). The results showed that all the three variables affect

booking intentions: a high level of severity is associated with a lower number of bookings,

and the effect is worsened in the case of a high degree of involvement and moderated in case

of observed agreement. Moreover, the effect of severity and agreement on hotel booking

intention can be mitigated by the presence of webcare, which can also create customers trust

toward the service provider, therefore increasing the intention to book.

Schuckert, Xianwei and Law (2015) analyzed the popularity and importance of online

reviews and how they changed during recent years. The methodology of the study used two

approaches: first, the Authors reviews all the relevant literature in the field of online reviews

to see the methods used and the results; second, they analyzed the limitations of the previous

studies, proposing directions for future analyses and what can still be developed. Two data

retrieval have been conducted in September 2013 and March 2014, with 50 articles found as

relevant to the study. The results of the analysis showed that review valence (i.e. the negative

or positive value of a review) has a strong effect on booking intentions; positive reviews in

terms of high ratings can also increase the possibility of revisit. Moreover, from the supply

perspective, managers can use reviews to assess additional information about the delivered

services; in particular, negative reviews can be an important mean of self-improvement. They

also concluded that managers’ response plays a critical role on the future revenues. The

Authors also addressed the motivations behind the writing of reviews by the users, showing

that the main reasons are to help potential travelers in access information, to provide

feedbacks, but also to stimulate future improvements in the services delivered. The Authors

also concluded that the trust people pose on the reviews depends on the website in which

these are written, but also on the number of helpfulness votes given to the review. Further,

also the personality of the reader, and the characteristics of the reviews appear to play a key

role.

Kwok, Xie and Richards (2017) study aims at making a synthesis of the literature in the

field on online reviews to understand the current trends and the knowledge gaps. Through an

analysis of the most recent publications, the Authors pointed out the importance of online

reviews in recent years and the areas where a further analysis is needed. The methodology

used is a literature review considering 67 research articles regarding online reviews, published

in the period from January 2000 and July 2015. The Authors were able to identify four themes

emerging from their academic reviews, which are: i) quantitative evaluation features; ii)

verbal evaluation features; iii) reputation features; and iv) social features. The results showed

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that reviews with extreme rating (i.e. five or one star) are perceived as more useful than

reviews with moderate ratings (i.e. two, three or four stars); and positive reviews have a more

positive impact on booking intentions that negative ones. Furthermore, in financial terms,

reviews have also an impact on the economy of the hotel: positive reviews are related to

higher prices, more sales, higher revenue per available room and higher market share.

Moreover, longer reviews contain more information and are more useful and reliable, and

positively influence consumers’ behavior; anyway, this theory is not supported by all the

studies in the field. Opposed theories believe that consumers will rely more on shorter,

essential and more readable reviews than ones containing too much information. Disclosure

and online reputation play a critical role in e-WOM, since they make a review more useful in

the eye of customers, assessing more credibility to the reviewer. Further, manager response is

determinant in both terms of problem solving and customer satisfaction increase, thus

transforming an unsatisfied customer into a loyal one.

Mauri and Minazzi (2013) wanted to investigate the existing relationship between hotel

guests’ reviews and consumer decision-making process and service expectations. The Authors

investigated the idea that hotel purchasing intentions by customers depend on the valence of

the review: purchasing intentions increase in case of a positive review and decrease in case of

a negative. Furthermore, the valence has also an influence on the level of expectations of the

customers: it is higher in case of positive review, and lower in case of negative. In addition,

the research question addressed whether hotel managers responses to reviews can influence

customers purchasing intentions and expectations. The research method used was the

collection of 349 questionnaires fr