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Agreeableness and perception of online hotel reviews
Anne-pim van Oostveen
Ondrej Mitas
Introduction
Online user-generated reviews about travel destinations, hotels, and tourism
services have become important sources of information for travelers (Pan,
MacLaurin, & Crotts, 2007), as each year hundreds of millions of potential
customers consult online reviews (Vermeulen & Seegers, 2009). Prominent
examples of consumer review platforms are websites such as Tripadvisor and
Booking.com. Millions of global travelers share their opinions regarding the quality
of hotels on these websites (Jeacle & Carter, 2011).
According to Chevlier and Mayzlin (2006), online user-generated content
substantially influences the sale of products. Their study suggests that the
influence of online consumer reviews is especially strong for experience goods such
as tourism products and services, because their quality intangible and unknown
prior to consumption. Thus, potential consumers use online consumer reviews as a
way to reduce risk and uncertainty during a purchase (Chen & Lee, 2008).
The consumer reviews found on travel and hospitality online communities
provide the customer with a view of another person’s a prior service experience.
These reviews reassure consumers that a business will deliver the service they want
(Sparks & Browning, 2011). However, consumer trust can also be negatively
affected, because websites also provide critical reviews.
Three-quarters of tourists consider online customer reviews as an important
information source when planning a trip (Gretzel & Xiang, 2010). Customers see
online customer reviews as relatively unbiased and more trustworthy than
marketing messages (Li & Bernoff, 2008). Ye, Law and Gu (2009) found that
positive online reviews leads to an increase in hotel bookings. However, research
suggests that negative information tends to have a stronger effect on customers ().
Furthermore, not all reviews have an effect, and not all potential customers are
affected equally.
Review sites such as TripAdvisor depend on their trustworthiness in order to
be successful. Mayer et al. (1995) argue that trust between two parties is based on
both the customer’s tendency to trust and the trustworthiness of the company to
be trusted. Trust is not just based on the general trustworthiness of the company,
but also on the tourist’s propensity to trust.
Whether someone tends to be trustful is part of their personality. In
psychology, personality is understood to be primarily defined by five dimensions,
the so-called ‘big five’: openness to experience, conscientiousness, extraversion,
agreeableness and neuroticism (John & Srivastava, 1999; Rose et al., 2010).
Agreeableness is the most important dimension with regards to trust. Agreeable
individuals tend to be ‘friendly, courteous, considerate, accommodating, tend to
avoid conflict, co-operative, helpful, forgiving and show propensity to trust’ (Tan &
Yang, 2013, p. 27).
Research has been done on how TripAdvisor and other websites that provide
online user-generated reviews try to engender trust (Jeagle & Carter, 2011).
However, little research has been conducted on the influence of customers’
propensity to trust and the perception of online reviews. In this article, I will
investigate the relation between the personality trait of agreeableness and the
perception of online hotel reviews.
Therefore, the main research question is: what is the relationship between
agreeableness and the perception of online hotel reviews? More specifically, I
examine the following sub-questions:
1. Is agreeableness positively related to use of online reviews before booking a
hotel?
2. Is agreeableness positively related to trust of online hotel reviews?
3. Is agreeableness positively related to booking flexibility in the presence of
positive reviews?
4. Is agreeableness positively related to booking willingness in the presence of
negative reviews?
Methods
To investigate the relation between agreeableness (independent variable)
and perception of online reviews (dependent variable), an online survey was
carried out.
Population and sample
The population for this study is defined as Dutch students who have Internet
access, use Facebook and are between the age of 18 and 25. This population was
selected for their availability and the fact that they are likely to use internet
applications such as review platforms.
Convenience sampling was used and data was collected using an online
survey facility (http://www.survio.com). The self-administered questionnaire was
published as a status update on Facebook. In total, 46 people answered the
questionnaire. Nine participants did not fit the population criteria and were
excluded from further analysis. Thus, the final sample size was 37. Of these
participants, 26 (70%) were women and 9 (30%) male. The fact that 70% of the
sample is female is a substantial diversion from the population of Dutch students,
which is nearly evenly divided by gender (48% vs. 52%; CBS, 2012, p. 101). As no
sampling frame was used, response rate could not be determined. However, 51% of
page visitors started and completed the questionnaire. All participants answered
all questions. For the purposes of the assignment, the total number of participants
was artificially inflated from 37 to 300 participants.
Questionnaire
The questionnaire consisted of three parts. The first part of the
questionnaire contained questions to find out participants’ level of agreeableness.
To measure this a 10-item short version of the Big Five Inventory was used
(Rammstedt & John, 2006, p. 210). The participant was asked to rate the
statements on personality on a five-point scale from “disagree strongly” to “agree
strongly”. Items 2 and 7 from the scale were used to measure agreeableness. The
polarity of question 7 was reversed.
The second part of the questionnaire consisted of questions on online review
perception and use. Items on this topic were specifically created for this research
since no available questionnaire items were found during literature review. A
seven-point scale from ‘never’ to ‘always’ was used to measure the frequency of
use of online reviews before booking a hotel. Subsequent items asked participants
to rate statements regarding online hotel reviews on a five-point scale from
‘disagree strongly’ to ‘agree strongly’.
To measure trust in online reviews, participants were asked to rate the
following on an agreement scale:
Online hotel reviews on websites such as TripAdvisor are…
1. Trustworthy?
2. Reliable?
To determine whether positive reviews would make choices of customers more
flexible, respondents were asked to rate the following trade-offs:
If the reviews of an hotel are very positive...
1. I’m willing to pay more money
2. I don’t mind a less favorable location
Finally, willingness to book in spite of negative reviews was measured with the
item: ‘When I read a negative review on the hotel I wanted to book I don’t let it
influence my decision.’ In addition to the research variables, the demographic
variables of gender, age and education were measured using a multiple-response
format.
Analyses
As all variables in this study were measured at the interval level and were
thus described in terms of means and standard deviations. I used Pearson
correlation tests to assess relationships between variables.
Findings
Descriptive findings are first reported for the main variables of
agreeableness, use of online reviews and trust. Subsequently, the relationship
between agreeableness and the dependent variables is investigated using
correlational analysis.
Agreeableness
Responses to two five-point scale questions from the big five inventory were
averaged (controlling for polarity) to measure agreeableness. The lowest possible
score for agreeableness was 1 and the highest 5. On average participants scored
3.70 on agreeableness. This is a slightly higher than a neutral score of 3. Standard
deviation for this variable was 0.75, indicating that the responses were relatively
close together.
Use of online reviews before booking a hotel
To measure use of reviews a seven-point interval scale was used. On
average, the participants scored 4.73. Thus, given that the midpoint of the scale is
4, many participants frequently use online reviews. The standard deviation was
1.67, indicating that the responses were neither far apart nor close together.
Trust in online reviews
To potentially increase reliability, responses to the two five-point scale
questions on ‘trustworthiness’ and ‘reliability’ of online reviews were averaged to
measure trust in online reviews. This new variable comprised an interval scale from
1 to 5. The mean response was 3.33, well above the midpoint of the scale.
Standard deviation for this variable is 0.77, indicating that the responses were
relatively close together.
Booking flexibility with positive reviews
Participants were asked about flexiblity related to price and location in the
presence of good reviews on a five-point scale. On average, the participants
reported mean flexibility of 3.05 concerning price and 2.84 concerning location.
Thus, participants are somewhat flexible in booking a positively-reviewed hotel.
The standard deviations regarding price and location were 0.96 and 0.97
respectively, indicating that the responses were relatively close together.
Willingness to book in spite of negative reviews
Participants rated their willingness to book a negatively-reviewed hotel on a
five-point scale. Participants reported an average willingess of 2.69, suggesting
ambivalence about booking in the face of negative reviews. The standard deviation
was 0.9, indicating that the responses were relatively close together.
Effects of agreeableness on review use and trust
Correlations are interpreted according to the following rules of thumb
(Bryman, 2012): any value above r = 0.5 is considered a large correlation, 0.3-0.5 is
moderate and 0.1-0.3 is small (<0.1 is negligible).
There was a small significant relation between agreeableness and use of
online hotel reviews (r = .12, p = .04). Participants who were more agreeable,
indicated that they made more use of online reviews. The correlation between
agreeableness and trust in online reviews was not significant (r = .06, p = .27).
To understand how positive reviews influence flexibility in booking a hotel
room, the participants were confronted with trade-offs about money and location.
The results show that participants who scored high on agreeableness were
significantly less likely to accept a higher price or a less favorable location when
presented with very positive reviews (price: r = -.19, p = .001; location: r = -.18, p
= .001). The correlation coefficients are negative with an absolute value between
0.1 and 0.3, indicating a small effect. This counterintuitive result will be
elaborated on in the discussion.
The questionnaire also included an item on how negative reviews influence
willingness to book a hotel. The results show that people who score high on
agreeableness are significantly less likely to disregard negative reviews in their
decision (r = -.37, p < 0.001). In other words, this moderate correlation showing
that highly agreeable people are more influenced by negative reviews.
Discussion
The present findings reveal the relation between agreeableness and the
perception of online hotel reviews. Previous research describes how review
websites try to create a trustworthy appearance (Jeagle & Carter, 2011). This
study adds to existing literature by investigating the trust relationship between
hotel review website and the customer from the customer perspective.
No significant correlation between agreeableness and trust in online hotel
reviews was found. This could be because a consumer’s personality structure does
not have much of an influence on their trust in online hotel reviews. However, the
results of the research show that there is a small correlation between
agreeableness and the use of online hotel reviews. This effect could be due to a
different aspect of the agreeableness trait than trust, such as valuing the opinions
of others (Tan & Yang, 2013).
Furthermore, findings show that there is a significant moderate correlation
between agreeableness and the influence of negative reviews. While a relationship
between agreeableness and trust of online hotel reviews in general was not found,
agreeableness may lead to a higher level of trust in negative reviews specifically.
Therefore, agreeable individuals might be quicker to believe negative reviews and
thus these reviews could have a bigger influence on the decision not to book a
hotel.
The finding showed that people who score high on agreeableness were
significantly less likely to accept a higher price or a less favorable location when
presented with very positive reviews on a hotel was counterintuitive. This might
be explained by the idea that agreeable people are more considerate (Tan & Yang,
2013, p. 27). Because they are more considerate they might consider other choice
criteria such as price and location as more important than a very positive review.
Limitations
A possible limitation of this study is that only two questionnaire items were
used to measure agreeableness. The items were taken from an already abbreviated
Big Five personality test. Therefore, the reliability of this study could have been
enhanced by asking participants to rate more items regarding agreeableness.
Furthermore, questions on online hotel review perception were not taken from
other scientific articles, because they were specific for this study.
Convenience sampling was used for this study, so the sample does not
represent the population. Only people who are my friends on Facebook were able
to fill in the questionnaire. My Facebook friends that are studying are not a
representative sample of the actual Dutch student population. Furthermore, the
nature of voluntarily filling in a questionnaire attracts and excludes certain types
of people from the sample.
A final point that is important to mention is the fact that declaring intention
is not the same as actually acting on it. People might choose answers in the
questionnaire that are different from their reaction when they are presented with
the same situation in real life. For example, people who say that they don’t let
negative reviews influence their decision on booking at a hotel, might actually be
highly influenced by a negative review when they have to make a real hotel
reservation that involves spending their own money in that moment.
Implications for the travel industry
There is a large body of research on tailoring website content to user
profiles (Calegari & Pasi, 2013; Pera & Ng, 2013; Bobadilla et al., 2012). User
profiles are constructed from digital data that is gathered by the website and
external third parties. By creating user profiles and sending tailored information
towards potential customers, online marketers can better target their marketing
messages. The user profile is a collection of data that represents the user’s
identity.
According to Klimstra et al, 2013, p. 213: ‘Personality is among the most
important factors contributing to individual differences in identity formation’.
Therefore, collecting data on a user’s personality is vital in creating a user profile.
This study can be seen as a first step in investigating the relation between
consumer personality and the perception of online hotel reviews. Commercial
enterprises such as TripAvisor and Booking.com could use this study as a blueprint
to investigate how consumers with a certain personality types react to the content
on their website. By knowing how a consumer will react to the content, the
content can be adjusted in order to create the desired reaction.
Combined with user profiling to find out the consumer’s personality, this
would create the opportunity to identify a consumer’s personality type and adjust
the content on the website based on his/her personality. On websites such as
TripAdvisor consumers would see tailored information that fits their personality
and will result in a reaction that has been researched before, much like approaches
increasingly taken by Facebook and OKCupid.
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Appendix
Questionnaire
SPSS Tables
