Jan. 2014. Vol. 3, No.5 ISSN 2307-227X
International Journal of Research In Social Sciences © 2013-2014 IJRSS & K.A.J. All rights reserved www.ijsk.org/ijrss
29
A MODEL OF DESTINATION BRANDING FOR IRANIAN HISTORICAL
CITIES
Kambiz Heidarzadeh Hanzaee, Hamid Saeedi
Department of Business Management, Science and Research Branch, Islamic Azad University,
Tehran, Iran
Hamid Saeedi ([email protected])
ABSTRACT
The current study aims to develop and test a theoretical model of destination branding, which integrates the
concepts of the branding , destination image, quality and loyalty. The study suggests historical image as a new
component of historical destination brand associations. Specifically, the current study examines the relationships
among brand associations for historical cities (i.e., historical, common, and unique image components), overall
brand image (i.e., overall image of a destination), perceived quality and tourists’ future behaviour. The target
population of this study was 750 domestic visitors, who stayed in shiraz, Isfahan, and Kermanshah (historical cities
in Iran). The results confirm that overall image is influenced by common image and is considered a critical
mediator between brand associations, Perceived quality and tourists’ future behaviour. In addition, historical image
had the first largest impact on the common image formation.
Keywords: historical Destination branding, Destination image, Brand image, Overall brand image, perceived
quality and loyalty
1. INTRODCUTION
In western asia, Iran is home to the most inscribed
sites in UNESCO1 with 16 sites. Armenian Monastic
Ensembles of Iran, Bam and its Cultural Landscape,
Bisotun, Golestan Palace, Gonbad-e Qābus, Masjed-e
Jāmé of Isfahan, Meidan Emam, Esfahan,
Pasargadae, Persepolis, Sheikh Safi al-din Khānegāh
and Shrine Ensemble in Ardabil, Shushtar Historical
Hydraulic System, Soltaniyeh,Tabriz Historic Bazaar
Complex, Takht-e Soleyman, chogha Zanbil, The
Persian Garden. The first sites to be recognized by
UNESCO from the west asia was Percepolis was a
city in ancient Persia. Every year, iran historical
cities accommodates a significant number of Iranian
1 United Nations Educational, Scientific and Cultural
Organization
and foreign tourists. Iran has a favorable climate and
many historical places Because of all these
attractions, we selected Shiraz, Isfahan and
Kermanshah (historical cities in iran) as our subject
of study. During the last two decades, both academia
and marketing practitioners have shown an increasing
interest in brand management. Branding is now
widely acknowledged asa potent tool for companies
to use to their advantage in achieving competitive
strengthen the market, as it generates value both for
the producer and consumers (Keller, 2008). the term
“destination branding” is recognised as that most
commonly used in tourism literature to describe the
method of creating a unique identity for a destination
that enables potential visitors to differentiate one
destination from another (Graves and Skinner, 2009).
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The core of destination branding is to build a positive
destination image that identifies and differentiates the
destination by selecting a consistent brand element
mix (Cai, 2002). Although not explicitly examined in
the context of branding, destination image should be
regarded as a pre-existing concept corresponding to
destination branding (Pike, 2009). The destination
branding literature, however, focuses primarily on
leisure and business tourism. There has been no
academic investigation into the branding of historical
places as centres. Destination images fall on a
continuum that begins with organic images which are
developed over a long period of time and represent
“the totality of what a person already knows or
perceives about that destination from newspapers,
radio and TV news, documentaries, periodicals,
dramas, novels, and non-fictional books and classes
on geography and history”(Gunn, 1997). A strong,
unique image is the essence of destination positioning
for its ability to differentiate a destination from
competitors to get into the consumers‟ minds, which
simplify information continuously (Botha, Crompton,
& Kim, 1999; Buhalis, 2000; Calantone, et al., 1989;
Chon, Weaver, & Kim, 1991; Crompton, Fakeye, &
Lue, 1992; Fan, 2006; Go & Govers, 2000; Mihalic,
2000; Mykletun, Crotts, & Mykletun, 2001; Uysal et
al., 2000).
The research first seeks to identify the key attribute
dimensions associated with destination historical
brand images and second, to assess the importance of
unique and common images attributes associated with
history. The focus of this paper is therefore not the
destination branding itself, but rather the destination
image concept, how that destination image is created,
communicated and controlled, and the relationship
between destination image and perceived quality and
loyalty. Each of these concepts will be explored
further in the paper.
2. LITERATURE REVIEW
2.1. branding theory
According to Kotler (1997) a brand is “a name, term,
sign, symbol, or design or combination of them
which is intended to identify the goods and services
of one seller or group of sellers and to differentiate
them from those of competitors.”Destinations are
similar to products and follow similar branding
processes. Consumers use brand names and product
attributes as retrieval cues for information about
product performance. Brand names and offering
attributes are the links to diagnostic information
about the product (Hutchinson & Alba, 1991). Keller
(1998) states that a physical good, a service, a retail
store, a person, an organization, a place and/or an
idea can be encompassed in the concept of product.
Branding has Viking origins. According to Keller
(2008) , the word „ brand ‟ is an Old Norse word
meaning „ to burn ‟ and refers to the practice of
marking animals by owners in order to identify them.
In the American Wild West, cowboys and ranchers
used a hot branding iron to singe, or “brand”. Today,
branding issued to imprint a representational image
of a product or service into the mind of the consumer.
There are various branding strategies applied to an
almost endless array of products and services.
Classical branding theory has been developed largely
in the context of consumer products (de Chernatony
and Segal- Horn, 2001). In this context, brands are
seen as complex entities (Gardner and Levy, 1955; de
Chernatony and Dall Olmo Riley, 1998).
For example, a place includes tangible attributes such
as historical sites or beaches as well as intangible
characteristics such as culture, customs, and history.
Because of the complex nature of a destination to be
a brand, generalization of the identity is inevitable.
Brand identity is critical for generalization of
desirable characteristics projected by supplier’s
perspective. It explains the expectations of a supplier
about how a brand should be perceived by its target
market. Defining a target market is crucial because
some aspects of a destination may seem positive to
one segment while ineffective to another (Fan, 2006).
2.2. Destination branding
Destination branding or the branding of places is a
field that has gained increasing attention over the last
decades. At least, a much cited article by Buhalis in
1999 stated that “the inadequacy of destination
marketing literature probably illustrates the interest
of researchers in the impacts of tourism on
destinations” (Buhalis, 2000). the concept of
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31
destination is very broad. They argue that a
destination can be everything that people visit for a
one day trip, a shorter stay or a longer holiday. In
addition, destinations can be owned, at one end of the
scale, by a single company whereas destinations, at
the other end of that scale, are constituted by
countries or regions (Moilanen &Rainisto 2009).
Although the concept of branding has been applied
extensively to products and services, the notion of
branding has only recently started to expand into
tourist destinations and became apparent as a topic of
examination in the late 1990’s (Tasci & Kozak, 2006;
Pike, 2004; Wagner & Peters, 2009).
2.3. Destination image
The definition of destination image is rather
problematic (Jenkins, 1999), and often avoided
(Echtner & Ritchie, 2003), since no consensus on
how to define a destination’s image has been reached
(Gallarza et al., 2002; Grosspietsch, 2006). Thus,
many definitions are quite vague, and, in several
cases, are not even explicitly stated (Echtner &
Ritchie, 1993, 2003; Fakeye & Crompton, 1991;
Beerli & Martin, 2004; Pike & Ryan, 2004). the
concept image remains complex and ill-defined in its
nature, since it has been described as: representation,
object, impressions, thoughts, ideas, beliefs, feelings
or identity. The most common and widely accepted
definition of brand image is “the perceptions about a
brand reflected as associations existing in the
memory of the consumer” (Keller,1993).
2.4. Historical image
Goeldner et al. (2000) suggest that history may be
one of the most interesting dimensions of a tourist
destination, and is a rich instrument which allows
creating a unique tourist experience. Local historic
sites, stories, and legends – all create a romantic and
lasting experience for region’s visitors .History is
also what differentiates and unites nations, and is one
of the important motives to visit one or another
region. Historic travels become much more popular,
and there are successful examples of how to use
history to create a brand image of a region. Examples
of popular historical attractions are Mount Vernon in
the USA (plantation home of President George
Washington, Virginia), Bastille square and Louvre in
Paris in Sweden – Vasa Ship in central
Stockholm(Goeldner et al., 2000). Complex image
can be derived as a result of direct experience of the
destination (Fakeye and Crompton, 1991). Since
Gunn‟s seminal work on destination image, many
researchers have defined and conceptualized
destination image in the context of tourism. Hunt
(1975) defined destination image as perceptions that
potential visitor should about a destination. When
measuring the destination image of Mexico held by
US citizens, Crompton (1979) conceptualized
destination image as the sum of cognitive beliefs and
affective impressions that an individual possesses of
a particular destination. Similarly, Baloglu and
Bringerg (1997) and Beerli et al. (2002) summarized
that destination image is characterized by subjective
perceptions that consist of both high levels of
cognitive aspects (belief) and affective aspects
(feeling). Therefore, it is deduced that:
H1: Historical image will positively affect common
image of a destination.
2.5. Unique image
The significance of unique image on overall image
warrants a need for more attention on this construct
from destination branding scholars. Interestingly, its
effect was even larger than the affective image
component, which has received more consideration
than unique image in the destination image literature.
The results of Qu et al. , research also show that
uniqueness of a destination has the second largest
influence on overall image. The importance of unique
image also lies in its usefulness to positioning the
destination brand. Because unique image is an
excellent source for differentiation (Echtner
&Ritchie, 1993), it needs to be identified and
emphasized to improve overall image and increase
the points of difference among various alternatives.
Thus, little attention has focused on the construct in
the literature, unique image should be considered as a
critical brand association to expand our knowledge
of destination image to the next level of destination
branding( Qu et al., 2011). It is proposed that there is
an additional image component to be considered as a
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32
brand association: unique image.Contrary to common
image, unique image is highlighted as a construct that
envisages the overall image of a destination (Echtner
& Ritchie, 1993). According to Echtner and Ritchie
(1993), the overall image of a destination should be
viewed and measured based on three dimensions of
attributes: holistic, functional psychological, and
unique-common characteristics. Uniqueness is
particularly important due to its influence on
differentiation among similar destinations in the
target consumers’ minds (Cai, 2002; Echtner &
Ritchie, 1993; Morrison & Anderson, 2002; Ritchie
& Ritchie, 1998). One of the purposes of branding is
to differentiate its product from those of competitors
(Aaker, 1991, p. 7). Hosting unique events can thus
lead to a differentiation of a destination‟s image and
products whichcan then emphasise and enhance the
uniqueness of a place (Buhalis 1999).Uniqueness
provides a compelling reason why travelers should
select a particular destination over alternatives.
Positive brand image is partly achieved through the
uniqueness of brand associations to the brand in
memory (Keller, 2008, p. 56). Thus, the unique
image of a destination is critical to establish the
overall image in the consumers’ minds. A strong,
unique image would increase the favorability of the
common image toward the destination. Therefore, it
is deduced that:
H2: Unique image will positively affect common
image of a destination.
2.6. Destination brand images
It is not surprising, therefore, that there is a
considerable literature on destination brand images
particularly in the area of leisure tourism marketing
(Walmsley and Young, 1998). Studies in this area
have focused upon the attributes forming destination
images. Several studies have sought to identify the
brand image attributes of specific tourism
destinations (Etchner and Ritchie ,1993). Others have
sought to identify common attributes across
destinations (Walmsley and Jenkins, 1993; Walmsley
and Young, 1998; Young, 1995). There has been
much debate on the relationship between brand and
image (Tasci & Kozak, 2006), however, one way in
which to classify brand image is, being a form of
consumer based brand equity (Pike, 2004). In this
sense, brand image can be defined as
being “The perception of a brand in the minds of
persons. The brand image is a mirror reflection
(though perhaps inaccurate) of the brand personality
or product being. It is what people believe about a
brandtheir thoughts, feelings, expectations”
(American Marketing Association, 2008). These
beliefs, or perceptions, are developed from the
associations or attributes that come to a consumer’s
mind when contemplating a particular brand (Shimp,
2007). Therefore, we propose a third hypothesis as
follows:
H3: Common image influence overall destination
brand image.
2.7. Perceived quality
Quality of service, from the perspective of Grönroos
(2000), is defined from two dimensions: the technical
quality (that which is delivered to the consumer) and
the functional quality of service (how it is delivered).
In contrast, Brady and Cronin (2001) state that the
perception on the quality of service is made up from
three dimensions: quality of results, quality of
interaction and quality of environment. Quality of
results is defined as that which the client obtains
when the productive process has finished, quality of
interaction is presented as the interaction which takes
place while service is being offered, and the quality
of environment as the background conditions where
the service is offered (or the product delivered).
Oliver (1997) states that every interpretation by the
consumer involves a relationship to a different kind
of expectation. Thus, we can define the variable
expectations as previous predictions or beliefs that
the consumer use to make about results or
performance of the product in the future (Olson and
Dover, 1979). According to Oliver (1997), the quality
of service is based on perceptions of excellence, so it
is logical to think that perceived quality is influenced
by the expectations of the consumer. Therefore, we
propose a fourth hypothesis as follows:
H4: overall destination brand image influence
perceived quality.
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2.8. Tourist behaviours
Previous research findings indicated that destination
image had both direct and indirect effect on
behavioural intentions (Alcaniz et al., 2009; Baloglu
and McCleary,1999; Bigne et al., 2001; Castro et al.,
2007; Chen and Tsai, 2007; Chi and Qu, 2008; Lee,
2009). In these studies, behavioral intentions were
usually examined from two different perspectives,
using the terms “intention to (re)visit and willingness
to recommend to others”. Conducting a SEM,
Baloglu and McCleary (1999) found that three
cognitive destination image factors (quality of
experience, attractions, and value/entertainment)
were positively associated with word-of-mouth (i.e.
willingness to recommend to others). Bigne et al.
(2001) investigated interrelationships among
destination image, perceived quality, satisfaction,
intention to return, and willingness to recommend to
others in the context of resort visitors. They found
that destination image had a direct effect on intention
to return and willingness to recommend to others.
Meanwhile, destination image was also found to have
an indirect effect on intention to return and
willingness to recommend to others through quality
and satisfaction. Chen and Tsai (2007) supported
Bigne et al,. (2001) findings by indicating that
destination image had a direct effect on trip quality
and behavioural intentions. In addition, destination
image had an indirect effect on behavioural intentions
through trip quality, perceived value, and satisfaction.
Recently, Alcaniz et al. (2009) also found a direct
effect of cognitive destination image on tourism
behavioural intentions. More specifically, functional
image was only related to revisit intention and
psychological image was only related to intention to
recommend, and mixed image was associated with
neither of the two behavioural intentions. Applying a
theory of market heterogeneity in their study, Castro
et al. (2007) found that there was strong an indirect
relationship between a destination image and
intention to visit, in which the relationship was
moderated by service quality and tourist satisfaction.
Chi and Qu (2008) tested a theoretical model that
examined whether or not destination image had a
direct or indirect effect on behavioural loyalty using a
sample of a famous spring tourists. The findings
indicated that destination image was indirectly related
to behavioural loyalty through attribute satisfaction
and overall satisfaction. Word-of-mouth (WOM) is
defined as “informal, person-to-person
communication between a perceived non-commercial
communicator and a receiver regarding a brand, a
product, an organization, or a service” (Harrison-
Walker, 2001, p. 63). Therefore, we propose a fifth
hypothesis as follows:
H5: perceived quality influence loyalty
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3.CONCEPTUAL MODEL
Figure I: Conceptual model
4. METHODOLOGY
4.1. Sampling
The target population of this study was domestic
visitors, who stopped at shiraz city ( pasargade and
persepolis), isfahan city (naghsh-e-jahan square and
jamee mosque), and Kermanshah (bisotun) all of
have been registered in UNESCO list of world
human heritage during an four-week period in August
and September 2013.
A confidence interval approach was used to
determine the sample size, suggested by Burns and
Bush (1995). With 50% of the estimated variability in
the population (Burns & Bush, 1995), the sample size
was set at 750 (n =750) at the 95% confidence level.
Every visitor who stopped at the five historical
attractions was approached to participate in the
survey. A random starting number for each day was
created. A set of questionnaires along with an
instruction letter was distributed to the five historical
attractions according to a proportionate subsample
size( 250) for each city.
4.2. Instrument
The survey questionnaire consisted of three major
sections. The first section included questions to
identify historical tourists. The second section was
developed to assess the respondent’s historical,
common, and uniqueness perceptions of overall
image toward Shiraz, Isfahan, and Kermanshah as a
travel destinations. To generate a complete list of the
respondent’s perceptions a method used by Qu etal.,
2011 was adapted. During the review of the literature
on destination branding and image measurement, all
the attributes used in the previous studies were
recorded and grouped by the researcher into a
“master list” of attributes. In addition, 20 expert in
marketing and tourism were held developing multi-
item scales capturing various aspects of Shiraz,
Isfahan, and Kermanshah image as a travel
Historical image
Common image
Unique image
Loyalty
Perceived quality
Overall
destination brand
image
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destinations. The last step was to have a panel of
university expert judges, who are academics and
practitioners in the areas of tourism, marketing, and
management examine the complete list of attributes
to eliminate redundancies and to add any missing
attributes. Finally, 19 items relating to historical
image, 24 items relating to common image and 8
items to unique image were selected and respondents
were asked to rate Shiraz, Isfahan, and Kermanshah
as a travel destinations on each of 51 attributes on a
5-point Likert scale where 1 =Strongly Disagree
(SD); 2= Disagree (D); 3=Neutral (N);4 =Agree (A);
and 5 = Strongly Agree (SA).
Affective image of destination was measured by
using affective image scales developed by Russel et
al. (1981) and Qu et al. (2011). The scale included
four bipolar scales:Arousing-Sleepy,Pleasant-
npleasant, Exciting-Gloomy, and Relaxing-
Distressing. A 7-point semantic-differential scale was
used for all four bipolar scales where the positive
poles were assigned to smaller values: 1= arousing
and 7 = sleepy, 1 =pleasant and 7 =unpleasant, 1=
exciting and 7= gloomy, and 1 =relaxing and 7 =
distressing. In addition, the scale of overall image
measurement was modified from Stern and Krakover
(1993). The respondents were asked to rate their
perception of overall image of Shiraz, Isfahan, and
Kermanshah on a 7-point scale with 1 being very
negative and with 7 being very positive. The next
section was to identify the attributes that make
Shiraz, Isfahan, and Kermanshah unique from Tehran
as capital city of Iran. A total of 8 items were derived
from the image study various travel literature and
confirm of experts. Although some of the similar
measures were used for capturing common and
unique images of Shiraz, Isfahan, and Kermanshah,
they should be considered as different measures
because common image measures the perceptions of
the general quality of tourist experiences in Shiraz,
Isfahan, and Kermanshah as a travel destination
(without any comparison with other destinations).
while overall image has more focus on comparison of
measures between Shiraz, Isfahan, and Kermanshah
and Tehran.
12 questions were included to determine the
perceived quality of Shiraz, Isfahan, and Kermanshah
brands that determine quality of historical
destination brand in mind of tourists. Additional 6
questions were included to determine the
respondent’s loyalty to Shiraz, Isfahan, and
Kermanshah and the respondent’s intention to
recommend Shiraz, Isfahan, and Kermanshah as a
favorable destinations to others with a 5-point Likert-
type scale (1 = most unlikely; 5 =most likely). The
final section was devoted to collecting demographic
information about the respondents. The last section
included questions relating to the individual travel
behavior of respondents and the information source
used prior to planning a trip to Shiraz, Isfahan, and
Kermanshah. The travel behavior items included the
number of times they visited Shiraz, Isfahan, and
Kermanshah , purpose for the trip, length of stay, and
total trip spending.
A pilot test was performed to assess how well the
survey instrument captured the constructs it was
supposed to measure, and to test the internal
consistency and reliability of questionnaire items.
The first draft of the survey instrument was
distributed to 40 randomly selected visitors who
stopped at isfahan. A total of 40questionnaires were
collected at the site. The results of the reliability tests
for each dimension showed that Cronbach’s alpha
was 0.80 for historical items, 0.87 for common items,
0.87 for uniqueness, 0.88 for overall destination
brand, 0.84 for perceived quality and 0.86 for
loyalty. The scale reliability was tested for internal
consistency by assessing the item-to-total correlation
for each separate itemand Cronbach’s alpha for the
consistency of the entire scale. Rules of thumb
suggest that the item-to-total correlations exceed .50
and lower limit for Cronbach’s alpha is .70
indicating above the minimum value of 0.70, which
is considered acceptable as a good indication of
reliability (Hair et al., 1998). Based on the results of
the pilot test and feedback from experts, the final
version was modified considering questionnaire
design, wording, and measurement scale.
4.3. Data analysis
Principal component analyses were used to determine
the underlying dimensions of the historical, common,
unique image, overall image of brand, perceived
quality and loyalty components of Shiraz, Isfahan,
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36
and Kermanshah. Confirmatory factor analysis and
SEM were utilized to test the conceptual model of
historical destination branding. the
data was processed with the statistical package SPSS
22.0 and AMOS 18.
5. RESULTS
5.1. Underlying dimensions of historical image
The result of Bartlett’s test of sphericity was
significant ( =2274.63, df= 120, KMO2= 0.767),
indicating that nonzero correlation existed. These two
tests suggested that the data was suitable for an
exploratory factor analysis. A principal component
analysis with orthogonal (VARIMAX) rotations was
assessed to identify underlying dimensions of
historical image. Based on the eigenvalue greater
than one, scree-plot criteria, and the percentage of
variance criterion, five components were chosen
which captured 56% of the total variance. Among the
19 image attributes, three items had communalities
less than .50 and factor loading less than .40. When
there are variables that do not load on any factor or
whose communalities are deemed too low, each can
be evaluated for possible deletion (Hair et al., 1998).
The results of the principle component analysis with
orthogonal (VARIMAX) rotations and rotated
component matrix are shown in Table 1. The scree
plot indicated that four factors may be appropriate;
however, based on a combination of scree plot and
eigenvalue greater than one approach, five factors
were retained. Components were labeled based on
highly loaded items and the common characteristics
of items they included. The component labels are
“Historical buildings” (Factor 1), “Service of
historical places” (Factor 2), “Historical knowledge”
(Factor 3), “Price and avaiability” (Factor 4), and
“Historical attraction” (Factor 5). These five factors
were later used to construct summated scales as
2 Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
independent variables for structural equation
modeling (SEM) for hypotheses testing.
5.2. Underlying dimensions of unique image
The results of a Kaiser-Meyer-Olkin Measure of
Sampling Adequacy (KMO) and Bartlett’s test of
sphericity indicated that unique image set was
appropriate for factor analysis( =558.18, df= 15,
KMO= 0.692). Based on the eigenvalue greater than
one, scree-plot criteria, and the percentage of
variance criterion, two factors were extracted through
principal component analysis with orthogonal
(VARIMAX) rotations was assessed to identify
underlying dimensions of unique image. The two-
factor model captured 55.3% of the total. A total of
two items had communalities less than .50 and factor
loading less than .40. Table 2 shows the results of the
principal component analysis with orthogonal
(VARIMAX) rotations. The scree plot indicated that
two factors may be appropriate. A combination of
scree plot and eigenvalue greater than 1 approach
selected three factors. Factors were labeled based on
highly loaded items and the common characteristics
of items they included. They are labeled as “Unique
customs of local people” (Factor 1)and “Unique
facilities of historical destination” (Factor 2) (Table
2). These two factors were later used to construct
summated scales as independent variables for
structural equation modeling (SEM) for hypotheses
testing.
5.3. Underlying dimensions of common image
The results of a Kaiser-Meyer-Olkin Measure of
Sampling Adequacy (KMO) and Bartlett’s test of
sphericity indicated that common image set was
appropriate for factor analysis ( =4046.23, df=
190, KMO= 0.830). Based on the eigenvalue greater
than one, scree-plot criteria, and the percentage of
variance criterion, five factors were extracted through
principal component analysis with orthogonal
(VARIMAX) rotations was assessed to identify
underlying dimensions of common image. The five-
factor model captured 55.8% of the total. A total of
four items had communalities less than .50 and
factor loading less than .40. Table 3 shows the results
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37
of the principal component analysis with orthogonal
(VARIMAX) rotations. The scree plot indicated that
five factors may be appropriate. A combination of
scree plot and eigenvalue greater than 1 approach
selected five factors. Factors were labeled based on
highly loaded items and the common characteristics
of items they included. They are labeled as
“Affective image” (Factor 1), “Local properties”
(Factor 2), “information and facilities” (Factor 3)
“Perception image” (Factor 4) “Cognitive image”
(Factor 5) (Table 3). These three factors were later
used to construct summated scales as independent
variables for structural equation modeling (SEM) for
hypotheses testing.
testing.
Table 1: Rotated Component Matrixa (historical image)
Component
Historical
buildings
Service of
historical
places
Historical
knowledge
Price and
avaiability
Historical
attraction
Q7_1 .813
Q8_1 .756
Q6_1 .610
Q9_1 .543
Q16_1 .816
Q17_1 .698
Q15_1 .648
Q12_1 .816
Q13_1 .774
Q11_1 .344 .500
Q5_1 .711
Q18_1 .655
Q14_1 .339 .632
Q2_1 .786
Q3_1 .660
Q1_1 .636
Table2: Rotated Component Matrixa(
unique image)
Component
Unique
customs of
local people
Unique
facilities of
historical
destination
Q41_1 .737
Q40_1 .683
Q42_1 .680
Q46_1
.782
Q44_1
.731
Q43_1 .349 .679
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38
5.4. Underlying dimensions of overall destination
brand image
The results of a Kaiser-Meyer-Olkin Measure of
Sampling Adequacy (KMO) and Bartlett’s test of
sphericity indicated that overall destination brand
image set was appropriate for factor analysis (
=3334, df= 45, KMO= 0.910). Based on the
eigenvalue greater than one, scree-plot criteria, and
the percentage of variance criterion, two factors were
extracted through principal component analysis with
orthogonal (VARIMAX) rotations was assessed to
identify underlying dimensions of overall image.
The two-factor model captured 55.3% of the total.
Only one item had communalities less than .50 and
factor loading less than .40. Table 4 shows the results
of the principal component analysis with orthogonal
(VARIMAX) rotations. The scree plot indicated that
two factors may be appropriate. A combination of
scree plot and eigenvalue greater than 1 approach
selected two factors. Factors were labeled based on
highly loaded items and the common characteristics
of items they included. They are labeled as
“Cognitive brand” (Factor 1) and “Historical brand”
(Factor 2) (Table 4). These two factors were later
used to construct summated scales as independent
variables for structural equation modeling (SEM) for
hypotheses testing.
Table3:Rotated Component Matrixa( common image)
Component
Affective
image
Local
properties
information
and facilities
Perception
image
Cognitive
image
Affective
image
Local
properties
information
and facilities
Perception
image
Cognitive
image
Affective
image
Local
properties
information
and facilities
Perception
image
Cognitive
image
Affective
image
Local
properties
information
and facilities
Perception
image
Cognitive
image
Affective
image
Local
properties
information
and facilities
Perception
image
Cognitive
image
Q66_1 .865 Q67_1 .853
Q69_1 .792
Q65_1 .758 Q68_1 .688
Q25_1 .784
Q22_1 .680 Q26_1 .648
Q21_1 .551
Q24_1 .535 Q37_1 .791
Q36_1 .775
Q38_1 .685 Q29_1 .743
Q28_1 .622
Q30_1 .552 .321 Q31_1 .536
Q34_1 .760
Q35_1 .662 Q33_1 .610
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39
5.5. Underlying dimensions of perceived quality
The results of a Kaiser-Meyer-Olkin Measure of
Sampling Adequacy (KMO) and Bartlett’s test of
sphericity indicated that perceived quality set was
appropriate for factor analysis( =746.62, df= 28,
KMO= 0.705). Based on the eigenvalue greater than
one, scree-plot criteria, and the percentage of
variance criterion, three factors were extracted
through principal component analysis with
orthogonal (VARIMAX) rotations was assessed to
identify underlying dimensions of perceived quality.
The three-factor model captured 58.5% of the total.
A total of four items had communalities less than .50
and factor loading less than .40. Table 5 shows the
results of the principal component analysis with
orthogonal (VARIMAX) rotations. The scree plot
indicated that three factors may be appropriate. A
combination of scree plot and eigenvalue greater than
1 approach selected three factors. Factors were
labeled based on highly loaded items and the
common characteristics of items they included. They
are labeled as “Overall satisfaction” (Factor 1),
“Perceived quality of services” (Factor 2) and ”
Perception of safety and services” (Factor 3) (Table
5). These three factors were later used to construct
summated scales as independent variables for
structural equation modeling (SEM) for hypotheses
testing.
5.6. Underlying dimensions of loyalty of tourist
The results of a Kaiser-Meyer-Olkin Measure of
Sampling Adequacy (KMO) and Bartlett’s test of
sphericity indicated that loyalty set was appropriate
for factor analysis ( =979.19, df= 15, KMO=
0.765). Based on the eigenvalue greater than one,
scree-plot criteria, and the percentage of variance
criterion, two factors were extracted through
principal component analysis with orthogonal
(VARIMAX) rotations was assessed to identify
underlying dimensions of unique image. The two-
factor model captured 61.7% of the total. Only one
item had communalities less than .50 and factor
loading less than .40. Table 6 shows the results of the
principal component analysis with orthogonal
(VARIMAX) rotations. The scree plot indicated that
two factors may be appropriate. A combination of
scree plot and eigenvalue greater than 1 approach
selected two factors. Factors were labeled based on
highly loaded items and the common characteristics
of items they included. They are labeled as
“Intention to repeat” (Factor 1)and “Intention to
recommend” (Factor 2), (Table 6). These two factors
were later used to construct summated scales as
independent variables for structural equation
modeling (SEM) for hypotheses testing.
Table 4:Rotated Component
Matrixa(overall image)
Component
Cognitive brand Historical
brand
o7_1 .804
o6_1 .774 o9_1 .760
o10_1 .745
o8_1 .731 o5_1 .668 .338
o4_1 .610 .429
o2_1 .780 o1_1 .762
o3_1 .744
Table5:Rotated Component Matrixa
(perceived quality)
Component
Overall
satisfact
ion
Perceive
d quality
of services
Perceive
d
quality of
services
Q48_1 .810
Q49_1 .700
Q47_1 .673
Q50_1 .785
Q51_1 .717
Q54_1 .538 .360
Q57_1 .796
Q56_1 .753
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40
Table6:Rotated Component Matrixa (
loyalty)
Component
Intention to repeat
Intention to recommend
Q59_1 .812 Q60_1 .793
Q62_1 .640
Q61_1 .613 Q64_1 .850
Q63_1 .789
5.7. Measurement model
Through principal component analyses, the five
underlying dimensions of historical image, the two
dimensions of unique image, the five dimensions of
common image, the two dimensions of overall
image, the three dimensions of perceived quality,
the two dimensions of loyalty were identified. There
is no reason to expect uncorrelated perceptions; thus
the factors are allowed to correlate as well (Hair et
al., 1998).
For purposes of CFA3 in this study, AMOS program
(version 18) was chosen to estimate the measurement
model and the construct covariances.
5.8. Confirmatory factor analysis
If correlations in the standardized solution exceed 1.0
or two estimates are highly correlated, one of the
constructs should be removed (Hair et al., 1998).
Based on this, for Confirmatory factor analysis of
historical image measurement model, one component
of historical image, which were greater than 1.0 was
deleted. The deleted component was “Historical
attraction”. The modified measurement model was
then re-estimated for assessing overall model fit. The
overall model fit statistics for the CFA were good (
= 168/7, df = 51, p < .05, GFI=.96, AGFI= .94, CFI=
.94, RMSEA= 0/056 ), indicating that the individual
indicators are behaving as expected.
3 Confirmatory Factor Analysis
For Confirmatory factor analysis of unique image
measurement model, one component of historical
image, which were greater than 1.0 was deleted. The
deleted component was “Historical attraction”. The
modified measurement model was then re-estimated
for assessing overall model fit. The overall model fit
statistics for the CFA were good ( = 144/7, df =
29, p < .05, GFI=.96, AGFI= .92, CFI= .96,
RMSEA=0/039), indicating that the individual
indicators are behaving as expected.
For Confirmatory factor analysis of common image
measurement model, The modified measurement
model was then re-estimated for assessing overall
model fit. The overall model fit statistics for the CFA
were good ( = 494/5, df = 165, p < .05, GFI=.93,
AGFI= .92, CFI= .91, RMSEA=0/052), indicating
that the individual indicators are behaving as
expected.
For Confirmatory factor analysis of overall image
measurement model, The modified measurement
model was then re-estimated for assessing overall
model fit. The overall model fit statistics for the CFA
were good ( = 144/7, df = 29, p < .05, GFI=.96,
AGFI= .92, CFI= .96, RMSEA=0/073), indicating
that the individual indicators are behaving as
expected.
For Confirmatory factor analysis of perceived
quality measurement model, The modified
measurement model was then re-estimated for
assessing overall model fit. The overall model fit
statistics for the CFA were good ( = 41/89, df =
15, p < .05, GFI=.98, AGFI= .96, CFI= .96,
RMSEA= 0/049), indicating that the individual
indicators are behaving as expected.
For Confirmatory factor analysis of loyalty
measurement model, The modified measurement
model was then re-estimated for assessing overall
model fit. The overall model fit statistics for the CFA
were good ( = 6/69, df = 4, p < .05, GFI=.98,
AGFI= .99, CFI= .99, RMSEA= 0/030), indicating
that the individual indicators are behaving as
expected. These results indicated that all variables
were significantly related to their specified
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41
constructs, verifying the posited relationships among
indictors and constructs.
5.9. Structural model
Based on the results of CFA, the structural model
was tested. The overall model fit statistics show that
the model is acceptable to represent the hypothesized
constructs ( = 5619/9, df = 1923 , p< .05, CFI=
.75, GFI= .79, AGFI= .77, RMSEA= .051). All the
paths proposed in the structural model were
statistically significant and of the expected positive
direction (Table 7). Thus, all five hypotheses failed to
be rejected
Figure II. Structural Model
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42
Hypothesis 1, the more positive historical image of a
destination, the more likely visitors would have the
positive common image of the destination, was failed
to reject ( β=0.772; tvalue =7/57; Sig. <0.01).
Hypothesis 2, the more positive unique image of a
destination, the more likely visitors would have the
positive common image of the destination, was failed
to reject ( β=0.604; tvalue =6/353; Sig. <0.01).
Hypothesis 3, the more positive common image of a
destination, the more likely visitors would have the
positive overall brand image of the historical
destination, was failed to reject ( β=0.279; tvalue
=5/410; Sig. <0.01). Hypothesis 4, the more positive
overall brand image of the historical destination, the
more likely visitors would have the positive
perceived quality of the historical destination, was
failed to reject ( β=0.310; tvalue =4/780; Sig.
<0.01). Hypothesis 5, the more positive perceived
quality of the historical destination, the more likely
visitors would have loyalty to the historical
destination, was failed to reject ( β=0.730; tvalue
=7/047; Sig. <0.01).
6. CONCLUSIONS AND
IMPLICATIONS
Destination branding is the set of marketing activities
that support the creation of a name, symbol, logo,
word mark or other graphic that readily identifies and
differentiates a destination (Blain et al., 2005). This
study analyzed the signification and importance of
historical destination branding, historical destination
image and the role of perceived quality and loyalty
in the destination branding for Iranian historical
destinations. Another aim of this study was to
examine the image of the Shiraz, Isfahan and
kermanshah by seeking to uncover perceptions and
attitudes towards the destination. As visitors seek out
differences in culture, heritage and landscape from
their everyday life when they choose a destination,
destinations should develop images based on their
unique features to differentiate themselves from their
competitors (Bramwell and Rawding, 1996). Insights
gained from these findings therefore provide
additional information to destination marketers in
developing the unique attributes of the Iranian
historical cities.
The purpose of this study was to develop a relatively
new concept of historical destination branding in the
marketing and tourism field by applying traditional
branding theory and practices to the Shiraz, Isfahan
and Kermanshah cities in order to build a unique and
favourable destination brand in the Iranian domestic
tourism market. Both researchers and practitioners
emphasize the importance of historical image
creation and destination differentiation as integral
elements in building a strong historical destination
brand. It was proposed that common destination
image (i.e., brand image) is a multi-dimensional
construct, influenced by the historical and unique,
images that collectively affect tourist behaviors.
However, based on research findings Historical
image of the tourist destination in Iran Historical
Image forming components include: historical sites,
the availability of tour guides, tours for historical
sites, Museums, Historical Buildings, Historical
Cemetery, historical mosques, knowledge of history,
historical Advertising, historical places brochure,
tours price, availability of historical places and
historical places ticket price. But unique image
components include: Museums, Historical
celebrations, historical architecture, historical
symbols, Culture, Natural attraction and
Hospitality.also common image components include:
Pleasant, exciting, friendly, Hospitality, lifestyles,
Security, natural landscape, music, health and
Handicrafts.
In spite of the fact that Shiraz is the first choice of
Iranian historical tourist, Isfahan is second and
Kermanshah is third. The findings provide historical
image have more impact on common image than
unique image. All research hypotheses were partially
supported. Results of this study have provided useful
strategic directions for the Iranian historical cities to
improve its destination competitiveness.
6.1. Limitations and further research
The findings and conclusion of this research should
be read consideration of several limitations.
First the population of this study was limited to
visitors who stopped at shiraz city ( pasargad and
persepolis), isfahan city (naghshe jahan square and
jamee mosque), and Kermanshah ( sang nebeshte
biston) all of have been registered in UNESCO4 list
of world human heritage during an four-week period
and It may not be generalizable for other historical
places in iran.
The second and main limitation of this research is
the credibility of the research findings based on the
4 United Nations Educational, Scientific and Cultural
Organization
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43
selected sample. Future research should be
undertaken using a bigger sample, for a better
understanding of the determinants of the destination’s
image and its relationship with the destination
branding.
Last, There may be other factors influencing the
historical brand image formation process and other
items that form the image of a destination. This study
is limited to including demoghraphic variables that
repeatedly appear in the literature.
We believe that historical destination branding
activities should also be focused on maintaining and
enhancing historical visitor loyalty to ensure long-
term destination success. As such, we suggest that
improve the historical knowledge, relationship
management techniques and practices designed to
strengthen visitor loyalty within the context of
destination branding could usefully be explored in
future studies. In the end, the historical image of a
city is central to its success (or failure) as a historical
destination but it needs to be related to other aspects
of the brand.
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