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“Personality and image as predictors of the intention to revisit and recommend
tourist destinations”
AUTH ORS
Jose Joel Cruz-Tarrillo
Karla Liliana Haro-Zea
Edison Effer Apaza Tarqui
ARTICLE INFO
Jose Joel Cruz-Tarrillo, Karla Liliana Haro-Zea and Edison Effer Apaza Tarqui
(2023). Personality and image as predictors of the intention to revisit and
recommend tourist destinations. Innovative Marketing , 19(1), 175-185.
doi:10.21511/im.19(1).2023.15
DOI http://dx.doi.org/10.21511/im.19(1).2023.15
RELEASED ON Monday, 20 March 2023
RECE IVED ON Monday, 19 December 2022
ACCEPTED ON Friday, 17 February 2023
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JOURNAL "Innovative Marketing "
ISSN PRINT 1814-2427
ISSN ONLINE 1816-6326
PUBLISHER LLC “Consulting Publishing Company “Business Perspectives”
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NUMBER OF REFERENCES
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NUMBER OF FIGURES
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© The author(s) 2023. This publication is an open access article.
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Innovative Marketing, Volume 19, Issue 1, 2023
http://dx.doi.org/10.21511/im.19(1).2023.15
Abstract
Undeniably, the new normality caused by COVID-19 presents an enormous challenge
for tourist destinations to become more attractive to visitors. us, the purpose of this
study is to analyze the impact of destination personality and image on tourist behavior
in Peru. is quantitative and cross-sectional analysis targeted 998 national tourists via
a non-probabilistic convenience sampling. e study employed AMOS 24 statistical
soware for exploratory and conrmatory factor analysis. e results showed posi-
tive eects of social innovativeness (β = 0.374), performance (β = 0.404), and honesty
(β = 0.191) on an aective image. Likewise, the study conrms the favorable eects of
social innovativeness (β = 0.524), performance (β = 0.156), and honesty (β = 0.280)
on a cognitive image. Furthermore, the eects of a cognitive image on the intention
to revisit (β = –0.756) and intention to recommend (β = –0.756) are also measured.
In addition, the ndings support the positive eects of an aective image in intention
to revisit (β = 1.549) and intention to recommend (β = 1.547); all results obtained a
signicance less than 0.05 (p < 0.001). is study concludes that brand personality
is a valuable concept that can suggest strategies to improve the brand image, so the
personality of tourist destinations should be congruent with the personality of tourists.
Jose Joel Cruz-Tarrillo (Peru), Karla Liliana Haro-Zea (Mexico),
Edison Eer Apaza Tarqui (Peru)
Personality and image as
predictors of the intention
to revisit and recommend
tourist destinations
Received on: 19 of December, 2022
Accepted on: 17 of February, 2023
Published on: 20 of March, 2023
INTRODUCTION
Tourism is considered as one of the most critical sectors of the econ-
omy that, thanks to the income of foreign currency and the gener-
ation of employment, contribute to the economic sustainability of a
nation (Stojčić et al., 2022). Around the world, tourism was forecast to
grow exponentially due to the increase in tourists (Purbadharmaja et
al., 2021). However, due to the COVID-19 pandemic, all tourism-relat-
ed economic activity suered signicant economic losses. As a result,
tourist destinations have gone through an unprecedented crisis, which
has altered tourist behavior to the point that many companies had to
close for not resisting the economic debacle. One way to boost them is
by improving the destination image.
Commercially, an image is inuenced by the brand personality that
destinations project toward tourists and interest groups; therefore,
managers should understand their brand personality to direct their
marketing strategies eciently. However, it must also be consistent
with the lifestyle and attitudes of consumers (Greene et al., 2022). us,
understanding tourist behavior is critical since it also depends on cul-
tural contexts (Wen et al., 2021). Peru oers many natural regions
(coast, mountains, and jungle), with customs, traditions, and lifestyles
© Jose Joel Cruz-Tarrillo, Karla Liliana
Haro-Zea, Edison Eer Apaza Tarqui,
2023
Jose Joel Cruz-Tarrillo, Ph.D. in
Business Administration, Research
Coordinator of the Professional School
of Administration, Faculty of Business
Sciences, Universidad Peruana Unión,
Tarapoto, Peru. (Corresponding author)
Karla Liliana Haro-Zea, Ph.D. in
Strategic Planning and Technology
Management, Popular Autonomous
University of the State of Puebla
(UPAEP); Research Professor,
Universidad Autónoma de Baja
California, Mexico.
Edison Eer Apaza Tarqui, Candidate
for a Master’s degree in Data Sciences,
Ricardo Palma University, Lima, Peru.
is is an Open Access article,
distributed under the terms of the
Creative Commons Attribution 4.0
International license, which permits
unrestricted re-use, distribution, and
reproduction in any medium, provided
the original work is properly cited.
www.businessperspectives.org
LLC “P “Business Perspectives”
Hryhorii Skovoroda lane, 10,
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BUSINESS PERSPECTIVES
JEL Classification M31, Z32, D12
Keywords marketing, tourist destinations, consumer behavior,
structural equation modeling
Conict of interest statement:
Author(s) reported no conict of interest
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that make certain places attractive and allow communication links with dierent environments (Li et
al., 2021). Derived from the above, the problem of this study is: what are the factors that inuence the
intention to revisit and recommend tourist destinations in Peru.
1. LITERATURE REVIEW
e concept of brand personality has been stud-
ied since 1950 (Ogilvy, 1955). Aaker (1997) dened
the structure and dimensions of brand personali-
ty, which determined a theoretical framework for
its measurement. Brand personality is a set of hu-
man characteristics associated with a brand that
constitutes an essential part of its identity. Brand
personality can also be applied to tourism destina-
tions (Hosany et al., 2007). e personality t of a
destination refers to the degree of correspondence
between the marketer’s and the consumer’s per-
ceptions (Kemp & Williams, 2012).
e brand of places and destinations represents a
growing research stream with signicant scope for
brand management and tourism (Hultman et al.,
2017). One is the tourist’s behavior, which has been
studied from dierent perspectives. Wu et al. (2017)
considered the adaptability behavior of the tourist.
Josiassen et al. (2022) viewed tourist anity and tour-
ist behavior. Barrientos et al. (2020) and McKercher
et al. (2015) researched the behavior of tourists in ur-
ban contexts and protected natural areas. Kvasova
(2015) studied ecological tourism behavior, Özdemir
and Yolal (2017) examined intercultural tourist be-
havior, and Vigolo (2017) – behavior of older tourists.
Brand personality aects both the cognitive and
emotional image of an institution. Cognitive im-
age aects customers’ perception of the brand
(Cam et al., 2019). Moreover, brand personality
has a substantial impact on the cognitive image
of customers. erefore, it is a crucial aspect for
the success of a brand, as customers can value a
destination based on their experience and knowl-
edge acquired during a trip, thus establishing a
connection with the brand (Cam et al., 2019). is
shows that the brand personality of a destination
inuences its image with customers through the
evaluations they make (Gnoth, 2002).
Phills et al. (2008) consider the terms of “social in-
novation” as new ways of addressing social prob-
lems that are more eective, ecient, sustainable,
or equitable than previous solutions. Its value cre-
ation depends on society rather than individuals.
ere is a close relationship between brand person-
ality and the emotional image that customers have
of the brand (Fournier, 1998). Brand personality
inuences customers’ emotional connection with
the brand, which strengthens its image. A strong
brand personality can generate positive emotions
in customers and make them feel that the brand
belongs to them. Brand personality is important
because it simplies customers’ decision-making,
allows them to express themselves through the
brand and establish relationships with the brand
(Hultman et al., 2017).
e tourism experience’s quality may signicant-
ly impact the intention to return to the establish-
ment and recommend it to others. is supports
the hypothesis that experience quality aects both
intentions (Sharma & Nayak, 2020). ese nd-
ings contradict previous studies in which expe-
rience quality does not impact loyalty intentions
in auent individuals (C.-F. Chen & F.-S. Chen,
2010). In addition, tourists’ attitudes determine
their compatibility with the online content of
tourism destinations, which may aect their clear
travel intentions (Amaro & Duarte, 2015).
On the other hand, the cognitive image of a brand
represents its overall quality and ability to meet
customer expectations and desires and impacts
recommendations and brand perception (Cam
et al., 2019). For example, a brand is only consid-
ered good if it meets and satises customer ex-
pectations. e intention to recommend is con-
sidered a behavior and indicator of customer loy-
alty or dissatisfaction (Baker & Crompton, 2000).
Furthermore, there is a correlation between cus-
tomer perceptions and intention to recommend,
linking the image of a tourism destination with
the purpose of the trip and the role of travel im-
agery in decision-making (Choi, 2011). erefore,
cognitive image aects how customers view the
brand and inuences their decision to recom-
mend it to others.
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When studying the brand image, it is not very easy
to dierentiate between the aective and cognitive
images because the aective image is the premise
of a cognitive image (Beerli & Martín, 2004). Loi
et al. (2017) researched the tourist transport ser-
vice in Macao and revealed that the destination’s
image predicts the intention to revisit it through
the satisfaction that the destination produces.
Allameh et al. (2015) showed that the destina-
tion’s image positively inuences the intention of
Iranian tourists to revisit this country as a sports
tourism center. Stylos et al. (2016) recognized the
positive eect of the cognitive image. erefore
tourists are more likely to select a destination with
a strong positive image.
Aective image is further linked to the custom-
er’s intention to recommend the brand (Cam et al.,
2019). is image reects customers’ emotions and
feelings toward the brand, ultimately leading to sat-
isfaction and the desire to recommend it to others.
In addition, the intention to recommend is oen
considered valuable information that can inuence
customer decision-making (Peter & Olson, 1983).
2. AIM AND HYPOTHESES
is study aims to determine the factors that in-
uence the intention to revisit and recommend
tourist destinations in Peru. Figure 1 shows the
theoretical model of this paper. Following the lit-
erature review, the study elaborated on the follow-
ing hypotheses:
H1: Performance has a signicant inuence on
the cognitive image of tourist destinations.
H2: Performance has a signicant inuence on
the aective image of tourist destinations.
H3: Social innovation signicantly inuences the
cognitive image of tourism destinations.
H4: Social innovation signicantly inuences the
aective image of tourism destinations.
H5: Honesty signicantly inuences the cognitive
image of tourism destinations.
H6: Honesty signicantly inuences the aective
image of tourist destinations.
H7: Cognitive image signicantly inuences the
intention to revisit tourist destinations.
H8: Cognitive image signicantly inuences the
intention to recommend tourist destinations.
H9: Aective image signicantly inuences the
intention to revisit tourist destinations.
H10: Aective image signicantly inuences the
intention to recommend tourist destinations.
3. METHODOLOGY
is is a quantitative and cross-sectional analysis.
e scale of Cruz-Tarrillo et al. (2022) was used to
measure brand personality, comprising 21 items
grouped into three dimensions (performance, so-
cial innovation, and honesty). e IMATUR in-
strument (Moraga et al., 2012) was adapted to the
research context, consisting of 14 items grouped
Figure 1. Theorecal model
H10
H9
H8
H7
H6
H5
H4
H3
H2
H1
Social
innovation
Honesty
Performance
Cognitive
image
Affective
image
Intention
to revisit
Intention
to recommend
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into two dimensions (aective and cognitive im-
ages) to measure the destination image. e scale
to measure tourist behavior was based on Žabkar
et al. (2010).
To elaborate the data, three stages were considered:
generation of the items, data collection, and con-
rmation of the latent structure (Kim et al., 2012).
For the generation of the items, an exhaustive
search was carried out in the literature; 12 profes-
sional managers and academics in the marketing
area evaluated the data. Subsequently, the content
validation is reviewed by a panel of seven experts
with an average of 20 years of experience in con-
sumer behavior who assessed the relevance, clarity,
consistency, and compliance with the Aiken coef-
cient indices. e tourist behavior scale com-
prised six items grouped into two dimensions. All
scales have 7-point response options, where “1” to-
tally disagrees, and “7” totally agrees, established
as the most convenient (Su & Reynolds, 2017).
3.1. Sampling and data collection
e literature oers various sampling procedures.
is study adopts the non-probabilistic tech-
nique for convenience. Although it is a common
technique (Ragb et al., 2020), obtaining enough
respondents is a viable option in terms of time,
speed, cost, and convenience (Abd Rahman et al.,
2015). e population consisted of national tour-
ists who had visited a tourist destination in Peru
during the period January-December 2021. In that
order of ideas, the study was conducted in 16 cities
in the three natural regions of Peru.
For information collection, a four-part online
survey was conducted on Google Forms. The
first section assesses the sociodemograph-
ic profile; the second comprises items of the
brand personality construct; the third – items
of the tourist destination image construct; and
the fourth section includes items of the tourist
behavior construct. Eight thousand two hun-
dred surveys were sent through social networks
such as WhatsApp, Instagram, Facebook, and
email from April to June 2021. A response rate
of 12.5% was obtained, that is, 1,026 surveys.
The exclusion criteria were applied to underage
tourists (< 18 years old) and to those who did
not manage to complete the questionnaire en-
tirety. Likewise, based on the multivariate dis-
tance measurement (Mahalanobis, 2018), eight
cases have been eliminated, leaving a final sam-
ple of 998 respondents.
3.2. Data analysis
To fulll the purpose of this study, the paper
adopted the structural equation modeling (SEM)
methodology using AMOS v24 soware, an ex-
tension of IBM SPSS v26. is soware tested the
model’s assumptions shown in Figure 1. In addi-
tion, the robust maximum likelihood method has
been applied to evaluate the model procedures
(Byrne, 2013).
Two stages were considered to estimate the meas-
urement and the structural models (Anderson &
Gerbing, 1988). In the rst, the theoretical mod-
el was created using conrmatory factor analysis
(CFA); in the second, the structural estimations
between constructs were performed to evaluate
the model and test the hypotheses. is multi-
variate technique models involve independent,
dependent, mediating, and moderating variables
(Hair et al., 2010).
4. RESULTS
According to the data collected from the 998 tour-
ists, 44% are men and 56% are women. ey are
primarily aged 18 to 25, with 68.8%. en, 20.8%
are in the age group of 26 to 35 years; 7.2% are in
the age group of 36 to 45 years; 2.3% are in the age
group of 46 to 55; and only 0.8% of tourists were
over 56 years old. Of the sample, 79% are univer-
sity students, 10.5% have completed postgraduate
studies, 9.8% have secondary education, and 0.7%
only have completed primary studies. Another
characteristic is that they mostly want to travel ac-
companied by family members (47.4%). However,
a considerable percentage prefer traveling with
their friends (24.4%) or partners (17%), and 11%
prefer solo trips.
4.1. Validation of constructs
Table 1 shows the construct validation of the
brand personality, tourist destination image, and
tourist behavior constructs. An exploratory factor
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analysis (EFA) was performed to examine the un-
derlying structure. In addition, the principal com-
ponent extraction method and Varimax rotation
were used (Kaiser, 1960).
For the brand personality construct, the Kaiser-
Meyer-Olkin (KMO) test showed a value of 0.979;
Bartlett’s sphericity test yielded a Chi-square of
36,320.54 and a signicance of 0.000 (p < 0.001),
grouped into three factors with a total explained
variance of 89.052%.
For the destination image construct, the KMO test
showed a value of 0.971; Bartlett’s sphericity test
gave a Chi-square of 25,441.40 and a signicance
of 0.000 (p < 0.001), grouped into two factors with
a total explained variance of 90.535%.
e construct of tourist behavior obtained a KMO
value of 0.943; Bartlett’s sphericity test yielded a
Chi-square of 10,891.29 and a signicance of 0.000
(p < 0.001), grouped into two factors with a total
explained variance of 95.254%.
Table 1. Conrmatory analysis values
Absolute t measurements Acceptable values Brand personality Desnaon image Tourist behavior
Chi-squared –921.57 349.107 95.397
P-value < 0.05 0.000 0.000 0.000
GFI ≥0.80 0.917 0.952 0.996
RMSEA ≤0.08 0.0 65 0.061 0.030
NFI > 0.90 0.975 0.986 0.999
CFI > 0.90 0.980 0.989 0.999
TLI > 0.90 0.976 0.987 0.999
IFI > 0.90 0.980 0.989 0.999
AGFI ≥0.80 0.892 0.931 0.987
Note: PE = Performance; IS = Social innovation; HO = Honesty; IC = Cognitive image; IA = Affective image; IV = Intention to
revisit; IR = Intention to recommend.
Figure 2. Conrmatory research model
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Generally, the KMO test values obtained for all
constructs were higher than 0.50 (Kaiser, 1974),
ensuring their suitability for EFA. In addition, the
P-value of the structure is 0.000 (p < 0.001), indi-
cating a signicant relationship between the var-
iables analyzed (Pan et al., 2017). CFA test was
performed for the instruments where the values
found were more signicant than the minimum
allowed (see Table 1).
A structural equation analysis (SEM) was per-
formed, whose indicators show a good model t
since a Chi-Square of 4,030.979 and a P-value =
0.000 was reached. Additionally, the t indices
reect acceptable values (GFI = 0.839; RMSEA =
0.066; NFI = 0.948; CFI = 0.957; AGFI = 0.816), so
the study proceeds to interpret the eects and re-
lationships that were found to contrast hypotheses
and achieve the objectives (Chaulagain et al., 2019).
e study conducted the content validation, for
which it was necessary to use the Aiken V coe-
cient, where values greater than 0.7 were obtained
(Aiken, 1985). Likewise, convergent validity ob-
tained a CR > 0.70, discriminant validity, and AVE
> 0.50, checking its position in the minimum es-
tablished theory (Priporas et al., 2020). On the
other hand, a reliability analysis used Cronbach’s
Alpha coecient, which yielded values greater
than α > 0.75. In this way, the conditions for ap-
plying the research instruments are met (Garanti
& Kissi, 2019).
Table 2. Instrument validaon
Instrument
items
Factor
loadings CR AVE Cronbach’s
alpha (α)
Aiken
(V)
Performance 0.983 0.854 0.984 0.92
Ecient 0.938
Compeve 0.930
Responsible 0.956
Strategist 0.938
Proacve 0.903
Producve 0.9 05
Friendly 0.928
Cozy 0.910
Helpful 0.923
Commied 0.909
Social innovaon 0.98 0.876 0.982 0.931
Collaborave 0.960
Tolerant 0.961
Entrepreneur 0.960
Creave 0.963
Instrument
items
Factor
loadings CR AVE Cronbach’s
alpha (α)
Aiken
(V)
Innovave 0.897
Clever 0.910
Aracve 0.897
Honesty .964 0.87 0.964 0.885
Generous 0.939
Fair 0.952
Transparent 0.933
Sincere 0.906
Cognive image 0.987 0.89 0.987 0.995
CIM1 0.955
CIM2 0.954
CIM3 0.961
CIM4 0.959
CIM5 0.933
CIM6 0.956
CIM7 0.959
CIM8 0.934
CIM9 0.934
CIM10 0.943
Aecve image 0.896 0.682 0.960 0.985
AIM1 0.951
AIM2 0.957
AIM3 0.869
AIM4 0.871
Intenon to
revisit 0.975 0.929 0.970 0.984
IRV1 0.947
IRV2 0.961
IRV3 0.962
Intenon to
recommend 0.981 0.946 0.985 1.000
IRC1 0.971
IRC2 0.952
IRC3 0.964
Note: CR = Composite reliability, AVE = Average variance
extracted.
4.2. Hypotheses testing
The study developed the model (Table 2) and
applied the structural equation method (SEM),
resulting in all the hypotheses of the structur-
al model being accepted (Table 3). As a result,
the effect of performance on a cognitive image
(H1) is positive with β = 0.156 and p < 0.001.
Furthermore, social innovation (H3) with β =
0.524 and p < 0.001 and honesty (H5) with β =
0.280 and p < 0.001 are predictors of a cognitive
image. On the other hand, performance (H2)
obtained β = 0.404, p < 0.001, social innovation
(H4) scored β = 0.374, p < 0.001, and honesty
(H6) had β = 0.191, p < 0.001; these variables are
predictors of an affective image.
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e cognitive image in the intention to revisit
(H7) showed β = –0.756, p < 0.001; the values indi-
cate a negative but signicant eect. On the other
hand, the intention to revisit (H9) with a β = 1.549,
p < 0.001 showed a signicant eect on the aec-
tive image. e cognitive image in the intention
to recommend (H8) obtained similar to H7 values,
β = –0.756, p < 0.001. Although the direct eect
of the aective image on the intention to recom-
mend (H10) is weak with β = 1.547, p < 0.001, it is
signicant and has the direction proposed in the
hypothesis.
5. DISCUSSION
Nine hundred ninety-eight tourists participated
in the survey; 68.8% are university students who
travel accompanied by a family member. Brand
personality and image positively or negative-
ly aect the intention to revisit and recommend
tourist destinations (Kim & Lee, 2015). is study
investigated brand personality, cognitive and af-
fective image, intention to revisit, and intention
to recommend Peruvian tourist destinations and
performed validity, exploratory, and CFA of the
constructs (Kim et al., 2012; Pereira et al., 2015).
Previous studies have considered the inuential
role of brand personality in the destination image
(Pong & Noor, 2015; Hosany et al., 2007; Priporas
et al., 2020; Chua et al., 2019; Garanti et al., 2019).
e ndings of this study conrm that among all
the constructs used, performance has positive ef-
fects on the aective image and social innovation
on the cognitive image. Hence, the study reinforc-
es the results of Papadimitriou et al. (2015), show-
ing positive and signicant eects of brand per-
sonality on brand image.
Along the same lines, the results maintain that na-
tional tourists, who have visited a tourist destina-
tion, attribute personality traits to the destination
such as ecient, competitive, responsible, strategic,
proactive, productive, friendly, welcoming, help-
ful, and committed; they boost a better percep-
tion of the aective image. Likewise, collaborative,
tolerant, entrepreneurial, creative, innovative, re-
sourceful, and attractive traits help to create a bet-
ter cognitive image (Aaker, 1997; Papadimitriou et
al., 2019; Blank et al., 2018; Zivanovic et al., 2017).
is study adopted the structure of the tourist
behavior constructs from Žabkar et al. (2010);
although it is valid, it had tourists as its unit of
analysis. According to the cultural aspect, the
behavior is dierent (Papadimitriou et al., 2015);
this study contributes and divides the construct
into two factors: intention to revisit and inten-
tion to recommend. A validation of the destina-
tion image construct designed by Moraga et al.
(2012) comprises many complementary factors
(functional benet, symbolic benet, hedonic
benet) that measure the destination image; for
this study, only two factors were sucient: aec-
tive and cognitive image (Stylidis, 2022). As a
result, the psychometric properties indicate that
the scale is valid (Table 1).
is study shows that the aective image compo-
nent is positively associated with tourist behavior;
when the destination is entertaining, lively, pleas-
ant, and cheerful, these signicantly aect tourist
behavior. is nding is similar to Carballo et al.
(2021), Sharma and Nayak (2019), Kusumawati et
al. (2020), Marques et al. (2021), and Tavitiyaman
et al. (2021), who found that the aective image
and other components positively aect the tourist
behavior.
Table 3. Path analysis
Research hypothesis Path Coecient p-value Decision
H1 Performance →Cognive image 0.156 *** Supported
H2 Performance → Aecve image 0.404 *** Supported
H3 Social innovaon →Cognive image 0.524 *** Supported
H4 Social innovaon → Aecve image 0 .374 *** Supported
H5 Honesty →Cognive image 0.280 *** Suppor ted
H6 Honesty → Aec ve image 0.191 *** Suppor ted
H7 Cognive image → Intenon to revisit –0 .756 *** Supported
H8 Cognive image → Intenon to recommend –0 .756 *** Supported
H9 Aecve image → Intenon to revisit 1.549 *** Supported
H10 Aecve image → Intenon to recommend 1.547 *** Supported
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erefore, this study shows how facilities, security,
the transportation system, signage, and customs
are components of the cognitive image that cause
adverse eects on tourist behavior. ese results
support Liang and Xue (2021), Nazir et al. (2021),
and Ragab et al. (2020), who demonstrated a chal-
lenge for marketers and managers in the tourism
industry and generated a need to make eorts to
promote tourist attractions to improve the image
and project a personality that is consistent with
that of a tourist. In this way, travelers will be more
engaged and motivated to visit a particular des-
tination, and a better economic return will be
obtained.
CONCLUSION
e objective of this study was to analyze the impact of brand personality and destination image on
tourist behavior. e study concludes that brand personality positively aects cognitive and aective
images. Likewise, an aective image has positive eects on tourist behavior. However, a cognitive image
was found to negatively aect tourist behavior.
is analysis contributes to the research on brand personality by proposing a structural model that
shows that brand personality and destination image factors aect tourist behavior. It also supports the
proposal of Aaker’s model on brand personality that can be applied to tourism destinations. However,
the study results did not fully replicate the structure of the ve dimensions. erefore, this analysis is
complemented by grouping the tourism behavior constructs into two dimensions.
e research results have practical implications for marketing decision-makers. First, the consumer
behavior scale could help to analyze tourist behavior. In uncertainty, it is necessary to understand the
cognitive and aective factors that inuence tourist destination personality. In this sense, this study is
signicant because it seeks to attract tourists to increase protability.
On the other hand, the results could help to diagnose destination personality traits and tourist
behavior, which are inputs to design marketing strategies for strategic positioning. Given that the
concern of a brand is always to remain current, attractive, and desirable to tourists, achieving this
challenge is complex and uncertain due to the constant variation in behavior, culture, and high
competition. Therefore, this study demonstrates that brand personality is a fundamental element
in marketing strategy since the personality of destinations must be consistent with the personality
of tourists.
AUTHOR CONTRIBUTIONS
Conceptualization: Karla Liliana Haro-Zea, Edison Eer Apaza Tarqui.
Data curation: Edison Eer Apaza Tarqui.
Formal analysis: Edison Eer Apaza Tarqui, Jose Joel Cruz-Tarrillo.
Investigation: Jose Joel Cruz-Tarrillo, Karla Liliana Haro-Zea.
Methodology: Jose Joel Cruz-Tarrillo, Karla Liliana Haro-Zea.
Project administration: Jose Joel Cruz-Tarrillo, Karla Liliana Haro-Zea.
Resources: Karla Liliana Haro-Zea, Jose Joel Cruz-Tarrillo.
Soware: Edison Eer Apaza Tarqui.
Supervision: Karla Liliana Haro-Zea.
Validation: Karla Liliana Haro-Zea, Jose Joel Cruz-Tarrillo.
Visualization: Karla Liliana Haro-Zea, Jose Joel Cruz-Tarrillo.
Writing – original dra: Karla Liliana Haro-Zea, Jose Joel Cruz-Tarrillo.
Writing – review & editing: Karla Liliana Haro-Zea, Jose Joel Cruz-Tarrillo.
183
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http://dx.doi.org/10.21511/im.19(1).2023.15
REFERENCES
1. Aaker, J. (1997). Dimensions
of brand personality. Journal
of Marketing Research,
34(3), 347-356. https://doi.
org/10.2307/3151897
2. Abd Rahman, A., Asrarhaghighi,
E., & Ab Rahman, S. (2015).
Consumers and halal cosmetic
products: Knowledge, religiosity,
attitude and intention. Journal of
Islamic Marketing, 6(1), 148-163.
https://doi.org/10.1108/JIMA-09-
2013-0068
3. Aiken, L. R. (1985). ree
coecients for analyzing
the reliability and validity
of ratings. Educational and
Psychological Measurement,
45(1), 131-142. https://doi.
org/10.1177/0013164485451012
4. Amaro, S., & Duarte, P. (2015). An
integrative model of consumers’
intentions to purchase travel
online. Tourism Management, 46,
64-79. https://doi.org/10.1016/j.
tourman.2014.06.006
5. Anderson, J. C., & Gerbing, D.
W. (1988). Structural equation
modeling in practice: A review
and recommended two-step
approach. Psychological Bulletin,
103(3), 411-423. https://doi.
org/10.1037/0033-2909.103.3.411
6. Allameh, S. M., Khazaei Pool,
J., Jaberi, A., Salehzadeh, R.,
& Asadi, H. (2015). Factors
inuencing sport tourists’ revisit
intentions. Asia Pacic Journal
of Marketing and Logistics, 27(2),
191-207. https://doi.org/10.1108/
APJML-12-2013-0159
7. Baker, D. A., & Crompton, J. L.
(2000). Quality, satisfaction and
behavioral intentions. Annals of
Tourism Research, 27(3), 785-804.
https://doi.org/10.1016/S0160-
7383(99)00108-5
8. Barrientos, R., Ascensão, F., &
D’Amico, M. (2020). Inappropriate
tourist behavior in protected
areas can lead to wildlife road-
kills. Animal Conservation, 23(4),
343-344. https://doi.org/10.1111/
acv.12547
9. Beerli, A., & Martín, J. D. (2004).
Factors inuencing destination
image. Annals of Tourism Research,
31(3), 657-681. https://doi.
org/10.1016/j.annals.2004.01.010
10. Blank, A. S., Koenigstorfer, J., &
Baumgartner, H. (2018). Sport
team personality: It’s not all about
winning! Sport Management
Review, 21(2), 114-132. https://doi.
org/10.1016/j.smr.2017.05.004
11. Byrne, B. M. (2013). Structural
equation modeling with EQS (2nd
ed.). New York: Routledge. https://
doi.org/10.4324/9780203726532
12. Cam, L. N. T., Nga, D. Q., &
Tianrungpaisal, T. (2019). Brand
personality and its moderating
impact on brand loyalty: e
empirical research of cafes in
Vietnam. Proceedings of the 2019
5th International Conference on
E-Business and Applications –
ICEBA 2019 (pp. 60-64). https://
doi.org/10.1145/3317614.3317635
13. Carballo, R. R., León, C. J., &
Carballo, M. M. (2021). e
impact of terrorist attacks
in cities on the relationship
between tourists’ risk perception,
destination image and behavioural
intentions. Cities, 119, 103382.
https://doi.org/10.1016/j.cit-
ies.2021.103382
14. Chaulagain, S., Wiitala, J., & Fu,
X. (2019). e impact of country
image and destination image
on US tourists’ travel intention.
Journal of Destination Marketing &
Management, 12, 1-11. https://doi.
org/10.1016/j.jdmm.2019.01.005
15. Chen, C.-F., & Chen, F.-S. (2010).
Experience quality, perceived
value, satisfaction and behavioral
intentions for heritage tourists.
Tourism Management, 31(1),
29-35. https://doi.org/10.1016/j.
tourman.2009.02.008
16. Choi, J. G., Tkachenko, T., &
Sil, S. (2011). On the destination
image of Korea by Russian tourists.
Tourism Management, 32(1),
193-194. https://doi.org/10.1016/j.
tourman.2009.12.002
17. Chua, B. L., Kim, H. C., Lee, S., &
Han, H. (2019). e role of brand
personality, self-congruity, and
sensory experience in elucidating
sky lounge users’ behavior. Journal
of Travel and Tourism Marketing,
36(1), 29-42. https://doi.org/10.10
80/10548408.2018.1488650
18. Cruz-Tarrillo, J., Haro-Zea, K.
L., Tarqui, E. E. A., & Turpo-
Chaparro, J. (2022). Design and
validation of the brand personality
scale in tourist destinations.
Innovative Marketing, 18(2),
1-12. https://doi.org/10.21511/
im.18(2).2022.01
19. Fournier, S. (1998). Consumers
and their brands: Developing
relationship theory in consumer
research. Journal of Consumer
Research, 24(4), 343-373. https://
doi.org/10.1086/209515
20. Garanti, Z., & Kissi, P. S. (2019).
e eects of social media brand
personality on brand loyalty in
the Latvian banking industry:
e mediating role of brand
equity. International Journal of
Bank Marketing, 37(6), 1480-1503.
https://doi.org/10.1108/IJBM-09-
2018-0257
21. Garanti, Z., Ilkhanizadeh,
S., & Kissi, P. S. (2019). e
impact of branding on tourists’
satisfaction and loyalty in Iran.
In Experiencing Persian heritage
(Bridging tourism theory and
practice, Vol. 10) (pp. 223-241).
Emerald Publishing Limited.
https://doi.org/10.1108/S2042-
144320190000010014
22. Gnoth, J. (2002). Leveraging
export brands through a tourism
destination brand. Journal of
Brand Management, 9(4), 262-280.
https://doi.org/10.1057/palgrave.
bm.2540077
23. Greene, T., Seet, C., Rodríguez
Barrio, A., McIntyre, D., Kelly, B.,
& Bragg, M. A. (2022). Brands
with personalities – Good for
businesses, but bad for public
health? A content analysis of
how food and beverage brands
personify themselves on Twitter.
Public Health Nutrition, 25(1),
51-60. https://doi.org/10.1017/
S1368980021001439
24. Hair, J., Anderson, R., Babin, B.,
& Black, W. (2010). Multivariate
data analysis (7th ed.). Pearson.
184
Innovative Marketing, Volume 19, Issue 1, 2023
http://dx.doi.org/10.21511/im.19(1).2023.15
25. Hosany, S., Ekinci, Y., & Uysal,
M. (2007). Destination image
and destination personality.
International Journal of Culture,
Tourism and Hospitality
Research, 1(1), 62-81. https://doi.
org/10.1108/17506180710729619
26. Hultman, M., Strandberg, C.,
Oghazi, P., & Mostaghel, R. (2017).
e role of destination personality
t in destination branding:
Antecedents and outcomes.
Psychology and Marketing, 34(12),
1073-1083.
27. Josiassen, A., Kock, F., &
Nørfelt, A. (2022). Tourism
anity and its eects on
tourist and resident behavior.
Journal of Travel Research,
61(2), 299-313. https://doi.
org/10.1177/0047287520979682
28. Kaiser, H. F. (1960). e
application of electronic
computers to factor
analysis. Educational and
Psychological Measurement,
20(1), 141-151. https://doi.
org/10.1177/001316446002000116
29. Kaiser, H. F. (1974). An index of
factorial simplicity. Psychometrika,
39(1), 31-36. https://doi.
org/10.1007/BF02291575
30. Kemp, E., Childers, C. Y.,
& Williams, K. H. (2012).
Place branding: creating
selfbrand connections and
brand advocacy. Journal of
Product & Brand Management,
21(7), 508-515. https://doi.
org/10.1108/10610421211276259
31. Kim, H.-b., & Lee, S. (2015).
Impacts of city personality
and image on revisit intention.
International Journal of Tourism
Cities, 1(1), 50-69. https://doi.
org/10.1108/IJTC-08-2014-0004
32. Kim, J. H., Ritchie, J. R. B.,
& McCormick, B. (2012).
Development of a scale to
measure memorable tourism
experiences. Journal of Travel
Research, 51(1), 12-25. https://doi.
org/10.1177/0047287510385467
33. Kusumawati, A., Utomo, H. S.,
Suharyono, S., & Sunarti, S. (2020).
Eects of sustainability on WoM
intention and revisit intention,
with environmental awareness
as a moderator. Management of
Environmental Quality, 31(1),
273-288. https://doi.org/10.1108/
MEQ-03-2019-0064
34. Kvasova, O. (2015). e Big Five
personality traits as antecedents
of eco-friendly tourist behavior.
Personality and Individual
Dierences, 83, 111-116. https://
doi.org/10.1016/j.paid.2015.04.011
35. Li, J., Nguyen, T. H. H., &
Coca-Stefaniak, J. A. (2021).
Coronavirus impacts on post-
pandemic planned travel
behaviours. Annals of Tourism
Research, 86, 102964. https://doi.
org/10.1016/j.annals.2020.102964
36. Liang, X., & Xue, J. (2021).
Mediating eect of destination
image on the relationship between
risk perception of smog and revisit
intention: A case of Chengdu. Asia
Pacic Journal of Tourism Research,
26(9), 1024-1037. https://doi.org/1
0.1080/10941665.2021.1941156
37. Loi, L. T. I., So, A. S. I., Lo, I. S.,
& Fong, L. H. N. (2017). Does
the quality of tourist shuttles
inuence revisit intention
through destination image
and satisfaction? e case of
Macao. Journal of Hospitality
and Tourism Management, 32,
115-123. https://doi.org/10.1016/j.
jhtm.2017.06.002
38. Mahalanobis, P. C. (2018). On
generalized distance in statistics
(Reprinted). e Indian Journal of
Statistics, 80(1_A suppl), S1-S7.
39. Malär, L., Nyenegger, B., Kroh-
mer, H., & Hoyer, W. D. (2012).
Implementing an intended brand
personality: A dyadic perspective.
Journal of the Academy of
Marketing Science, 40(5), 728-744.
https://doi.org/10.1007/s11747-
011-0251-8
40. Marques, C., Vinhas da Silva,
R., & Antova, S. (2021). Image,
satisfaction, destination and
product post-visit behaviours:
How do they relate in emerging
destinations? Tourism
Management, 85, 104293.
https://doi.org/10.1016/j.tour-
man.2021.104293
41. McKercher, B., Shoval, N., Park, E.,
& Kahani, A. (2015). e [limited]
impact of weather on tourist
behavior in an urban destination.
Journal of Travel Research,
54(4), 442-455. https://doi.
org/10.1177/0047287514522880
42. Moraga, E. T., Artigas, E. A.
M., & Irigoyen, C. C. (2012).
Development and proposal of a
scale for measuring the image of
touristic destinations (IMATUR).
Review of Business Management,
14(45), 400-418. https://doi.
org/10.7819/rbgn.v14i45.1349
43. Nazir, M. U., Yasin, I., & Tat, H.
H. (2021). Destination image’s
mediating role between perceived
risks, perceived constraints, and
behavioral intention. Heliyon, 7(7),
e07613. https://doi.org/10.1016/j.
heliyon.2021.e07613
44. Ogilvy, D. (1955). e image of the
brand – A new approach to creative
operations (6 p.). e Courtesy of
Ogilvy & Mather. Retrieved from
https://www.markenlexikon.com/
texte/ogilvy_the-image-of-the-
brand_1955.pdf
45. Özdemir, C., & Yolal, M.
(2017). Cross-cultural tourist
behavior: An examination of
tourists’ behavior in guided tours.
Tourism and Hospitality Research,
17(3), 314-324. https://doi.
org/10.1177/1467358415589658
46. Pan, L., Zhang, M., Gursoy, D.,
& Lu, L. (2017). Development
and validation of a destination
personality scale for mainland
Chinese travelers. Tourism
Management, 59, 338-348.
https://doi.org/10.1016/j.tour-
man.2016.08.005
47. Papadimitriou, D.,
Apostolopoulou, A., & Kaplanidou,
K. (K.). (2015). Destination
personality, aective image,
and behavioral intentions
in domestic urban tourism.
Journal of Travel Research,
54(3), 302-315. https://doi.
org/10.1177/0047287513516389
48. Papadimitriou, D., Kaplanidou,
K., Alexandris, K., & eodorakis,
N. (2019). e brand personality
of professional football teams: A
rened model based on the Greek
professional football league. Sport,
Business and Management, 9(5),
443-459. https://doi.org/10.1108/
SBM-03-2018-0021
185
Innovative Marketing, Volume 19, Issue 1, 2023
http://dx.doi.org/10.21511/im.19(1).2023.15
49. Pereira, R. L. G., Correia, A.,
& Schutz, R. L. A. (2015).
Golf destinations’ brand
personality: e case of the
Algarve. International Journal
of Culture, Tourism, and
Hospitality Research, 9(2), 133-153.
https://doi.org/10.1108/IJC-
THR-05-2014-0037
50. Peter, J. P., & Olson, J. C.
(1983). Is science marketing?
Journal of Marketing,
47(4), 111-125. https://doi.
org/10.1177/002224298304700412
51. Phills, J. A., Deiglmeier, K., &
Miller, D. T. (2008). Rediscovering
social innovation. Stanford Social
Innovation Review, 6(4), 34-43.
Retrieved from https://ssir.org/
articles/entry/rediscovering_so-
cial_innovation#
52. Pong, K., & Noor, S. (2015).
e inuence of destination
personality on brand image
evaluation among archaeological
tourists. Jurnal Komunikasi:
Malaysian Journal of
Communication, 31(1), 133-152.
https://doi.org/10.17576/jkm-
jc-2015-3101-07
53. Priporas, C. V., Stylos, N., &
Kamenidou, I. (E.). (2020). City
image, city brand personality
and generation Z residents’ life
satisfaction under economic
crisis: Predictors of city-related
social media engagement. Journal
of Business Research, 119, 453-
463. https://doi.org/10.1016/j.
jbusres.2019.05.019
54. Purbadharmaja, I. B. P., Setiawan,
P. Y., Hayashi, T., & Widanta, A.
A. B. P. (2021). How electronic
word of mouth (e-WOM)
triggers intention to visit through
destination image, trust and
satisfaction: e perception of
a potential tourist in Japan and
Indonesia. Online Information
Review, 45(5), 861-878. https://doi.
org/10.1108/OIR-03-2019-0111
55. Ragab, H., Mahrous, A. A., &
Ghoneim, A. (2020). Egypt’s
perceived destination image
and its impact on tourist’s
future behavioural intentions.
International Journal of Tourism
Cities, 6(2), 449-466. https://doi.
org/10.1108/IJTC-12-2018-0105
56. Ragb, H., Mahrous, A. A., &
Ghoneim, A. (2020). A proposed
measurement scale for mixed-
images destinations and its
interrelationships with destination
loyalty and travel experience.
Tourism Management Perspectives,
35, 100677. https://doi.
org/10.1016/j.tmp.2020.100677
57. Sharma, P., & Nayak, J. K.
(2019). Do tourists’ emotional
experiences inuence images
and intentions in yoga tourism?
Tourism Review, 74(3), 646-665.
https://doi.org/10.1108/TR-05-
2018-0060
58. Sharma, P., & Nayak, J. K. (2020).
Examining experience quality
as the determinant of tourist
behavior in niche tourism: An
analytical approach. Journal of
Heritage Tourism, 15(1), 76-92.
https://doi.org/10.1080/174387
3X.2019.1608212
59. Stojčić, N., Mikulić, J., & Vizek, M.
(2022). High season, low growth:
e impact of tourism seasonality
and vulnerability to tourism on
the emergence of high-growth
rms. Tourism Management, 89,
104455. https://doi.org/10.1016/j.
tourman.2021.104455
60. Stylidis, D. (2022). Exploring
resident – Tourist interaction and
its impact on tourists’ destination
image. Journal of Travel Research,
61(1), 186-201. https://doi.
org/10.1177/0047287520969861
61. Stylos, N., Vassiliadis, C. A.,
Bellou, V., & Andronikidis, A.
(2016). Destination images,
holistic images and personal
normative beliefs: Predictors
of intention to revisit a
destination. Tourism Management,
53, 40-60. https://doi.org/
https://doi.org/10.1016/j.tour-
man.2015.09.006
62. Su, N., & Reynolds, D. (2017).
Eects of brand personality
dimensions on consumers’
perceived self-image congruity
and functional congruity with
hotel brands. International Journal
of Hospitality Management, 66,
1-12. https://doi.org/10.1016/j.
ijhm.2017.06.006
63. Tavitiyaman, P., Qu, H., Tsang,
W.-s. L., & Lam, C.-w. R. (2021).
e inuence of smart tourism
applications on perceived
destination image and behavioral
intention: e moderating role
of information search behavior.
Journal of Hospitality and
Tourism Management, 46, 476-
487. https://doi.org/10.1016/j.
jhtm.2021.02.003
64. Vigolo, V. (2017). Older tourist
behavior and marketing tools.
Springer International Publishing.
https://doi.org/10.1007/978-3-
319-47735-0
65. Wen, J., Kozak, M., Yang, S., & Liu,
F. (2021). COVID-19: Potential
eects on Chinese citizens’
lifestyle and travel. Tourism
Review, 76(1), 74-87. https://doi.
org/10.1108/TR-03-2020-0110
66. Wu, L., Zhang, J., Lu, Q., & Rah-
man, A. B. M. S. (2017). Tourist
adaptation behavior in response
to climate disasters in Bangladesh.
Journal of Sustainable Tourism,
25(2), 217-233. https://doi.org/10.
1080/09669582.2016.1195837
67. Žabkar, V., Brenčič, M. M., &
Dmitrović, T. (2010). Modelling
perceived quality, visitor
satisfaction and behavioural
intentions at the destination
level. Tourism Management, 31(4),
537-546. https://doi.org/10.1016/j.
tourman.2009.06.005
68. Zivanovic, M., Cerovic, S., &
Bjekic, J. (2017). A six-factor
model of brand personality.
Psihologija, 50(2), 141-155. https://
doi.org/10.2298/PSI161031002Z
