Stepchenkova morrisontm revisitingechtner

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Tourism Management ] (]]]]) ]]]–]]]
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Russia’s destination image among American pleasure travelers:
Revisiting Echtner and Ritchie
Svetlana Stepchenkovaa, Alastair M. Morrisonb,Ã
a
Department of Hospitality and Tourism Management, Purdue University, 154 Stone Hall, 700 W. State Street, West Lafayette, IN 47907-2059, USA
b
Department of Hospitality and Tourism Management, Purdue University, 111A Stone Hall, 700 W. State Street, West Lafayette, IN 47907-2059, USA
Received 23 May 2006; received in revised form 8 June 2007; accepted 13 June 2007

Abstract

This study measured Russia’s destination image among US pleasure travelers by the means of a Web-based survey. The methodology
proposed by Echtner and Ritchie [(1993). The measurement of destination image: An empirical assessment. Journal of Travel Research,
31(Spring), 3–13] was enriched by using a combination of two software programs, CATPAC and WORDER, to analyze responses to
open-ended questions about stereotypical holistic, affective, and uniqueness images and facilitate statistical comparisons of images
between visitors and non-visitors to Russia. A favorability variable was operationalized on the textual data, and affective images of
visitors and non-visitors to Russia were statistically compared. The study found that American travelers’ perceptions of Russia were
often negative and there is a lack of awareness about Russia’s destination features. Marketing implications for Russia’s Federal Travel
Agency based on the study results are discussed.
r 2007 Published by Elsevier Ltd.

Keywords: Affective image; CATPAC; Content analysis; Destination image; Russia; Stereotypical holistic image; Uniqueness image; WORDER

1. Introduction areas, complicated visa procedures, rising prices for tour
packages, and lack of advertising. To realize its tourism
Russia is a vast country with rich tourist resources of all potential, the country needs not only to solve the above-
kinds. They include unique natural features, beautiful mentioned problems but also to attractively present itself
landscapes, historical and cultural attractions, places of to international travelers. To become a competitive global
ethnographic interest, and good recreational opportunities. destination, the Federal Tourism Agency of Russian
However, while Russian outbound and internal tourism Federation (FTA) needs to develop Brand Russia which
have been growing rapidly, inbound tourism is growing would ﬁrmly position the country among the competitive
slowly and for the several years has been suffering from destinations of Eastern Europe and Asia. Given the size of
political instability associated with terrorist activity in the US tourist market and the fact that US pleasure
Russia; therefore, income from international tourism is a travelers are the world’s leading travel spenders (WTO,
small share of Russia’s overall economy (Russia’s State 2006a), this segment is very attractive for the Russian
Statistics Service (Rosstat), 2006). Since the 1990s, Russia tourism industry from an economic standpoint.
has been successfully developing its tourist offer; never- To be successfully promoted in a particular market, ‘‘a
theless, some problems still remain. Among the factors that destination must be favorably differentiated from its
prevent faster growth of Russia’s inbound tourism are a competition, or positively positioned, in the minds of the
lack of infrastructure, especially in the country’s eastern consumers’’ (Echtner & Ritchie, 2003, p. 37). A desirable
differentiation and positioning can be achieved by a
ÃCorresponding author. Tel.: +1 765 494 7905; fax: +1 765 496 1168. destination’s marketing organization by creating and
E-mail addresses: svetlana@purdue.edu (S. Stepchenkova), managing the perceptions, or images, that potential
alastair@purdue.edu (A.M. Morrison). travelers hold about the destination. Therefore, the purpose

0261-5177/$ - see front matter r 2007 Published by Elsevier Ltd.
doi:10.1016/j.tourman.2007.06.003

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and.... Tourism Management (2007), doi:10.1016/j.tourman.2007.06.003

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of this study was to examine Russia’s destination image 2004). Strong support for cognitive interpretation of image
among US pleasure travelers by investigating the following as a set of relevant attributes is given by Gensch (1978):
questions: ‘‘Products seldom are measured or evaluated as single lump
sum entities; rather, it is the attributes of the alternatives
1. What stereotypical holistic images do US pleasure that are measured, compared, and form the basis for
travelers associate with Russia? choice’’ (cited in Gartner, 1986, p. 636). This view was
2. What affective images does Russia as a travel destina- further supported by Engel, Blackwell, and Miniard (1986),
tion evoke? who stated that image is the consumer’s subjective
3. What unique places and features do US pleasure perceptions, which refer to how an alternative performs
travelers associate with Russia? on important evaluative criteria.
4. What are US pleasure travelers’ perceptions of Russia’s Social and environmental psychological tradition re-
destination attributes? gards cognition and affect as interrelated elements, where
5. Does the degree of familiarity with Russia (visitors/ affect is largely dependent on cognition (references to this
non-visitors) affect the destination image of Russia? view can be found in Baloglu & McCleary, 1999).
However, Russell and Snodgrass (1987, p. 246) argued
The lack of information is evident: a destination image that ‘‘behavior may be influenced by the (estimated,
literature review conducted by Pike (2002) for the period of perceived, or remembered) affective quality of an environ-
1973–2000 found that only one out of 142 articles had dealt ment rather than by its objective properties directly’’. The
with Russia’s image, and this study by Pizam, Jafari, and affective component of destination image expresses feelings
Milman (1991) reflected the old, ‘‘Soviet’’ image of the toward a destination, which can be favorable, unfavorable,
country. The analysis of Russia’s destination image as held or neutral. Gartner (1993) suggested that the affective
by US pleasure travelers should be useful to both the FTA component comes into play at the stage when different
and Russian travel providers, to see how Russia is travel alternatives are evaluated. Furthermore, there are
perceived by one of the largest tourist markets in the recent indications that emotions might be better predictors
world, and to counter negative or inaccurate perceptions of of behavior than perceptual evaluations (Yu & Dean,
potential visitors. 2001). Despite its obvious importance, affect has generally
been overlooked by destination image researchers: only six
2. Study background out of 142 studies surveyed by Pike (2002) studied affective
images.
2.1. Destination image construct Gartner (1993), Pike and Ryan (2004), and White (2004)
among other scholars, also recognized a third—conative or
The concept of ‘‘image’’ that has been studied for several behavioral—element in the destination image construct,
decades in such disciplines as social and environmental which is related to how travelers act toward a destination
psychology, marketing, and consumer behavior, was on the basis of the cognition and affect they have about it.
introduced into tourism studies in the early 1970s by Hunt Conation reflects a likelihood of destination selection, or
(1971), Mayo (1973), and Gunn (1972) and has since brand purchase, and can be interpreted as a propensity to
become one of the most researched topics in the field. visit a destination within a certain time frame (Pike &
However, as meta-analyses of destination image studies Ryan, 2004). The conative element of destination image is
indicated (Chon, 1990; Gallarza, Saura, & Garcia, 2002; influenced by both the cognitive and affective components.
White, 2004), due to its complexity, subjectivity, and Familiarity plays an important role in destination image
elusive nature, the concept of destination image has been formation. It influences destination perceptions and
interpreted differently by various researchers. The view on attractiveness and represents a key marketing variable in
destination image as an overall impression is rooted in segmenting and targeting potential visitors (Baloglu, 2001).
psychological tradition and consumer behavior theory Familiarity can be understood as previous experience with
(Assael, 1984; Herzog, 1963) and was supported by Hunt a destination (experience dimension) and knowledge about
(1971) and Reilly (1990). However, operationalization of it (informational dimension). One stream of research on
the destination image construct without breaking it into familiarity and destination image compares pre- and post-
separate, more evaluative elements is problematic. Tourism visitation destination images. Phelps (1986) recognized
scholars generally agree that destination image holds at secondary destination images, as formed by travelers’
least two distinctive components—cognitive and affective exposure to different information sources, and primary
(Baloglu & Brinberg, 1997; Baloglu & McCleary, 1999). images, which are created after actual visitation. Her
The cognitive, or perceptual, element refers to knowledge research, as well as the studies done by Pearce (1982), Chon
and beliefs about a destination, while the affective element (1991), and Dann (1996), suggested that visitation affects
refers to feelings about a destination. images and changes some of the perceptions about a
Despite the composite nature of the destination image destination. Post-visitor perceptions were found to be more
construct, in most destination image studies researchers positive than those of pre-visitors. However, there are
have emphasized the cognitive dimension (Pike & Ryan, indications that a relationship between visitation and

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destination images is more complicated. Pizam et al. (1991) Altogether, the holistic component is positioned as a
studied pre- and post-images of a group of US students who mental picture, or overall representation, of the destina-
visited the Soviet Union, and found that, basically, the tion, and, as such, resembles the overall component of the
images stayed the same. The other stream of research destination image. The holistic component is important for
determined how destination images differed between visitors understanding how a particular destination is categorized
and non-visitors (Ahmed, 1991; Chon, 1991; Milman & in the minds of consumers, and what prevailing images and
Pizam, 1995) or non-visitors, first-timers and repeat visitors stereotypes are associated with a given destination. In the
(Fakeye & Crompton, 1991). Images of visitors tend to be following sections of this article, images derived from the
more favorable; however, no significant differences were answers to these two questions are referred to as
found between perceptions of first-time and repeat visitors. ‘‘stereotypical’’ and ‘‘affective’’, respectively. The unique-
This suggested that most changes in destination image occur ness dimension is assessed by the item:
during the first visitation. Therefore Hypothesis 1 was
formulated to answer research question 5: ‘‘Please list any distinctive or unique tourist attractions
Hypothesis 1. ‘‘US residents who have visited Russia have that you can think of in _______’’.
more favorable images of the destination than those who
have not’’. This component is very important for differentiating a
destination from a competitive set of destinations, and will
2.2. Conceptualization by Echtner and Ritchie (1991) be further referred to as the ‘‘uniqueness image’’.
Thus, Echtner’s and Ritchie’s approach lies within the
In the whole body of destination image studies, Echtner cognitive-affective-overall image tradition and is consistent
and Ritchie (1991, p. 11) proposed a somewhat unique with MacKay’s and Fesenmaier’s (1997, p. 538) view that
conceptualization of the destination image construct based ‘‘a destination image is a composite of various products
on an extensive review of the literature on destination (attractions) and attributes woven into a total impression’’.
image research for the period of 1975–1990: Echtner and Ritchie (1993) suggested a conceptual frame-
work for operationalization of all specified components of
‘‘Destination image should be envisioned as consisting destination image, as well as proposed a convenient
of two main components; those that are attribute-based format for visual representation of image components. In
and those that are holistic. designing the scale for measuring the attribute-based
Each of these components of destination image contains items, Echtner and Ritchie followed the framework
functional, or more tangible, and psychological, or more proposed by Churchill (1979) for marketing studies. Steps
abstract, characteristics. such as specifying the domain of the image construct,
Images of destinations can also range from those based generating a sample of items, purifying the measures using
on ‘‘common’’ functional and psychological traits to Cronbach’s alpha as an indicator, and iterative factor
those based on more distinctive or even unique features, analysis were conducted. Thus, the issues of content
events, feelings or auras’’. validity, dimensionality, and internal consistency reliability
(Peter, 1979) of the proposed scale were addressed by the
The attribute-based component is captured by a series of researchers.
scale items that range from tangible, or functional
(beaches, shops, sports facilities, etc.), to more intangible, 3. Methodology
or psychological (receptiveness of local people, quality of
service, etc.). These attributes also represent a common 3.1. Destination image measurement
dimension of a destination, since every destination can be
evaluated on the basis of these general criteria. The holistic The composite nature of the destination image construct
component is captured by two open-ended items (Echtner presents great challenges for its measurement. Strong
Ritchie, 1991, p. 11): preference has been given to structured methods when
data were obtained as answers to close-ended survey
‘‘What images or characteristics come to mind when you questions (Pike, 2002). While structured methodologies
think of _______ as a travel destination? have a number of advantages over qualitative methods,
How would you describe the atmosphere or mood that they focus on particular destination attributes and gen-
you would expect to experience while visiting _______?’’ erally neglect the holistic aspect of destination image.
Qualitative studies, on the contrary, are helpful in
The first question is functional, while the second one is measuring the holistic aspect, but do not facilitate
more psychologically oriented. Responses to the second statistical and comparative analyses of destination images
item include affective evaluations, such as exciting, (Jenkins, 1999). Echtner and Ritchie’s (1993) methodology
relaxing, boring, etc., and, therefore, resemble the Baloglu framework provided a much needed balance between
and Brinberg (1997) affective component (White, 2004). quantitative and qualitative aspects of image measurement.

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This research closely followed the methodology suggested misspellings, synonyms, and multi-word concepts have to
by Echtner and Ritchie (1993) with regard to the be taken into account (Woelfel, 1998); however, the necessary
quantitative analysis of the destination image, and took changes should concern only the meaningful words, or image
their approach a step further with respect to the qualitative variables in our case. WORDER has a built-in function that
image assessment. It is not the purpose of this study to allows making changes in the data by means of the input
provide an extended literature review of the qualitative table, simultaneously with the counting process. The details
methods that have been employed in the analysis of of the CATPAC-WORDER approach can be found in
destination images—an extensive overview can be found Stepchenkova, Kirilenko, and Morrison (2006).
in Ryan and Cave (2005). However, it should be noted that The computer-assisted approach employed in this study
content analysis of textual and/or pictorial materials by for content analysis of textual responses to three image
Reilly (1990), Echtner and Ritchie (1993), Dann (1996), questions (stereotypical, affective, and uniqueness) provides
MacKay and Fesenmaier (1997), Andsager and Drzewiecka a more detailed assessment of destination image and
(2002), Echtner (2002), and Ryan and Cave (2005), among facilitates statistical comparisons of images among different
others, employed sorting and categorization techniques to groups of respondents, thus enriching the destination image
identify the frequencies of certain words, concepts, objects, measurement methodology proposed by Echtner and
or people, and treated the most frequent ones as image Ritchie (1993). The application of CATPAC-WORDER
variables. The final set of image variables can contain software combination discussed above and a way to
nouns, verbs, and descriptors (i.e., adjectives and adverbs), compare favorability of affective images in order to test
since nouns are used to focus attention on attractions (e.g., Hypothesis 1 discussed in Section 4.2 is considered a
museums, Lake Baikal), verbs describe actions or tourism contribution of this study from the methodology standpoint.
types (e.g., rafting, sightseeing), and descriptors (e.g.,
ancient, exciting) create atmosphere (Echtner, 2002). The 3.2. Research instrument
analysis can be computer-assisted (e.g., Ryan Cave, 2005)
The original questionnaire (Echtner, 1991), with two items
or done by hand, and identified image variables are then
for each of 35 attributes, was obtained. It was decided to use
often placed on a plane or a line along specified dimensions
only one item per attribute for this study. Two attributes,
to provide image visualization (Echtner Ritchie, 1993).
namely, degree of urbanization and extent of commercializa-
The large volume of textual data in qualitative studies
tion were thought to be better applicable to small destinations
and the repetitiveness of the task made the computer a
and were excluded. An accommodation/restaurants attribute
natural and powerful choice for content analysis despite
was split into two separate items, since accommodation
the fact that not all nuances of the language can be
shortage is a known problem for the Russian tourist sector,
recognized by any given software program (Alexa Zuell,
but the situation is much better with restaurants.
2000). For content analysis of open-ended questions, this
Prior to this research, the authors conducted two
study used a combination of two software programs,
exploratory studies to gain insights into induced and
CATPAC (Woelfel, 1998) and WORDER (Kirilenko,
organic aspects of Russia’s destination image (Stepchen-
2004) in order to answer research questions 1, 2, 3 and 5
kova, Chen, Morrison, 2007; Stepchenkova Morrison,
and test Hypothesis 1 not only on attribute-based items but
2006). In addition, five travel professionals and seven
on textual responses as well. CATPAC has been employed
‘ordinary’ people were asked to provide answers to the
for more than a decade in content analysis of political
three Echtner’s and Ritchie’s open-ended questions on
speeches, focus group interviews, marketing studies, and
Russia’s image. As a result of these prior efforts, seven
destination images to ‘‘identify the most important words
Russia-specific attributes (cruises, combined trips, non-
in a text and determine patterns of similarity based on the
capital Russia, fishing and hunting, unique natural
way they are used in text’’ (Woelfel, 1998, p. 11) and also
resources, Trans-Siberian railroad, and arts) were added
because of its strong visualization capabilities. However,
to the questionnaire. Three general attributes—namely,
CATPAC analyzes only one textual file at a time.
good quality food, chance to see how people really live, and
WORDER software was developed to process in one run
knowing something of a country’s history—were also
up to 1000 files of similar type (e.g., survey responses,
included in the survey with the phrasing taking from
newspaper articles, etc.) and count the number of specified
Crompton (1977) for a research purpose which is not
key words/image variables in every one of them. Ultimately,
explained in this article due to a space constraint. To
the approach used in this study allows: (1) identification
ensure clarity of the survey instrument, the phrasing of
of destination image variables in digital textual data using
attribute items was borrowed, when possible, from Echtner
CATPAC, and (2) counting the occurrences of these
(1991) and tested in July 2005 by a group of graduate
variables in every textual survey response with WORDER.
students from a large Midwestern university.
The result is a two-dimensional data matrix, which can be
easily transferred into any statistical package for further 3.3. Population and data collection
statistical analysis and clustering purposes.
Normally, a laborious ‘‘smoothing out’’ procedure The survey population came from one of the America’s
should be performed on the textual data prior to analysis: oldest and largest private travel clubs (further referenced as


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ATC), serving tens of thousands of families in many states Overall, the open-ended questions produced fewer
($75 000 members, 30 000 households, predominantly in responses than the attribute statements: question Q1 about
the Midwest) at the time when the study was conducted. stereotypical image (What images or characteristics come
ATC members with Internet access (about 20 000) were the to mind when you think of Russia as a travel destina-
sample frame for this research, and a random sample of tion?)—316; question Q2 about affective image (How
5000 e-mail addresses was selected from the ATC database. would you describe the atmosphere or mood that you
These people were sent an e-mail from the ATC manage- would expect to experience while visiting Russia?)—313;
ment team with the request to take part in the study. and question Q3 about uniqueness image (Please list
The data were collected during three weeks in July–August any distinctive or unique tourist attractions that you
2005. One hundred and eighty-nine responses were can think of in Russia.)—273. Eleven respondents
obtained in the first round. A follow-up letter was sent chose to give the same answers to questions Q1 and Q2
a week later, and 148 responses were collected in the or Q1 and Q3, putting in the answer field ‘‘See above’’,
second round. There were no differences between the 1st ‘‘Same as #1’’, or ‘‘See #1’’, and substitutions were made as
and 2nd round respondents for all the demographic indicated. A certain percentage of respondents chose not to
variables, except income. The aggregated profile of the submit some of the demographic data; predictably, the
respondents is given in Table 1. The total number of highest number of refusals was for the income question
Russia’s Destination Image Survey Website hits was (14.6%). There were a number of responses that contained
503, the total number of submitted responses was 341, missing values for one or a few attributes; however, the
the number of usable responses was 337. These IP number of missing entries was small relative to the
addresses were checked to ensure that there were no sample size, and the responses with missing entries were
double entries. kept in the data.

Table 1
Respondents’ profile

Variable Levels Whole sample Variable Levels Whole sample

Frequency % Frequency %

Visitation Visitors 54 16.0 Age 18–24 1 0.3
Non-visitors 283 84.0 25–34 8 2.4
Total 337 100.0 35–44 29 8.6
Friends and/ Yes 31 9.2 45–54 74 22.0
or relatives No 306 90.8 55–64 130 38.6
in Russia Total 337 100.0 65 and older 86 25.5
Gender Male 147 44.0 PNTA 9 2.6
Female 187 56.0
Total 334 100.0 Total 336 99.7
Education High school 19 5.6 Marital Single 47 13.9
Some college 53 15.7 status Married 252 74.8
Associate 24 7.1 With a partner 4 1.2
Bachelor 105 31.2 Widowed 27 8.0
Master 93 27.6 PNTA 7 2.1
Ph.D. 40 11.9
PNTAa 3 0.9
Total 337 100.0 Total 337 100.0
Job Administrative 20 5.9 Income Less than $30 000 6 1.8
Educator 21 6.2 $30 000–$49 999 24 7.1
Executive 21 6.2 $50 000–$74 999 48 14.2
Managerial 20 5.9 $75 000–$99 999 58 17.2
Professional 87 25.8 $100 000–$149 999 81 24.0
Sales/marketing 14 4.2 $150 000–$199 999 31 9.2
Self-employed 24 7.1 $200 000 and above 41 12.2
Student 1 0.3 PNTA 48 14.2
Retired 111 32.9
Other 15 4.5
PNTA 3 0.9
Total 337 100.0 Total 337 100.0
a
PNTA—prefer not to answer.


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4. Results factors. The factor ‘‘great food’’ was eliminated as the
result of this check and due to a low reliability alpha.
4.1. Research question 1: stereotypical holistic images Another concern was that the stable word combinations
produced by factor analysis did not account for large
By following the CATPAC-WORDER procedure de- differences in frequencies between words combined in some
scribed in the previous section, a list of 72 most frequent of the image factors, e.g., in Factor 9, the word ‘‘old’’ had a
meaningful words was obtained using CATPAC. Some frequency of 25, while the ‘‘buildings’’ word’s frequency
words, e.g., ‘‘history’’, ‘‘historic’’, ‘‘historical’’ or ‘‘large’’, was 39. It meant that at least 14 occurrences of the word
‘‘big’’, were grouped together under the most frequent ‘‘buildings’’ were used in other word combinations.
name, in this case ‘‘history’’ and ‘‘large’’, to reinforce Therefore, factors, which contained words with large
concepts, and substitutions in the data were made by differences in frequencies, were checked against the original
WORDER. Second, the frequencies of every specified data as well. As a result, some high frequency words, e.g.,
stereotypical image variable were counted in every response ‘‘poor’’, were associated with such words as ‘‘lodgings/
using WORDER. Table 2 contains overall frequencies of accommodations’’, which were not originally included into
Russia’s stereotypical image variables. the stereotypical image variables set. Finally, some image
The next step was to reduce the number of stereotypical factors were combined together, since they belonged to the
image variables to a smaller number of image concepts by same image concepts, e.g., Factors 4 and 8 made one
means of factor analysis. The dataset, which was obtained holistic image of ‘‘orthodox churches with onion-shaped
by WORDER, had 45 variables and 317 cases, which gave domes’’, which was used in many responses. The final
a solid case to variable ratio of 7.04 (Kline, 1994). Principal results of Russia’s stereotypical holistic images are given in
Components Analysis with Varimax rotation was used. Table 3.
Since textual responses were generally very short, e.g.,
‘‘Cold. Beautiful churches’’, it was decided to look for
stable word combinations, which might include as few as Table 3
two words, rather than for full 3–5 word factors. There- Stereotypical holistic images
fore, the number of factors was not specified and the # Stereotypical holistic images
option ‘‘Eigenvalues larger than 1’’ was chosen. Weak
items (‘‘dark’’, ‘‘interesting’’, and ‘‘exotic’’) with low 1 Cold weather, snow
2 Beautiful architecture and old buildings
coefficients in the diagonal of the anti-image matrix
3 Poor people, country, lodgings, and food choices
(o0.40), low communalities (o0.50) and those that did 4 Historic sites and places
not load higher than 0.35 on any factor were eliminated 5 Moscow, Red Square, and Kremlin
(Kline, 1994). The remaining variables produced 17 factors 6 St. Petersburg, Hermitage, palaces, and museums
that explained 67% of the total variance. 7 Vast country with lots of open spaces
8 Beautiful countryside
The factor solution produced was an intermediate step to
9 Orthodox churches with onion-shaped domes
identify the final stereotypical holistic images. Guided by 10 Big cities, interesting old cities
this solution, the factors were checked against the original 11 Great culture, different culture
data in order to ensure that word combinations containing 12 Beautiful music, ballet, art
descriptive items such as cold, beautiful, poor, old, large, 13 Friendly/unfriendly people
14 Volga River
great, vast, friendly, different, were not used in a negative
15 Vodka
context, which would entirely change interpretability of the

Table 2
Stereotypical image variables

Variable Frequency Variable Frequency Variable Frequency Variable Frequency

Cold 69 Kremlin 24 Food 12 Orthodox 7
Beautiful 55 Palaces 23 Culture 12 Open 7
People 54 Weather 19 Friendly 12 Vodka 6
History 45 Museums 19 Domes 10 Exotic 6
Buildings 39 Churches 19 Countryside 10 Sites 6
Poor 38 Cities 18 Snow 9 Volga 5
Architecture 37 Large 15 Hermitage 9 River 5
Red Square 36 Interesting 13 Music 9 Spaces 5
St. Petersburg 34 Onion 13 Winter 9 Ballet 5
Moscow 30 Art 13 Dark 8
Country 28 Great 12 Different 8
Old 25 Vast 12 Places 7


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4.2. Research questions 2 and 5: affective images and averaged across the 36 remaining responses (Cronbach’s
favorability analysis alpha 0.786). The frequencies of each image variable were
counted by WORDER in every one of 337 textual files, and
To get insights into Russia’ affective images, the 337 the ‘‘favorability’’ values were computed for every response
textual responses to question Q2 were evaluated for by simply adding together all occurrences of positive and
favorability in order to test Hypothesis 1 not only for negative image variables multiplied by their score. The
attribute-based items but on the textual responses as frequencies of all affective image variables along with their
well. Using CATPAC, the study identified all evaluative favorability scores are given in Table 4.
descriptors (around 240) in the textual data provided To calculate the favorability value for the response:
by respondents, and combined them into 42 groups by ‘‘Fascinating country. Overall, people are friendly but
synonymous meanings, as suggested by thesauri, context, reserved. Boring nightlife, dull food, though’’, the follow-
and expert opinions. One word for each group, usually the ing procedure was implemented. The averaged favorability
most frequent one, was selected as an affective image scores for all affective image variables in the response (1.97
variable. The final set of image variables contained mostly for ‘‘fascinating’’, 1.92 for ‘‘friendly’’, 0.08 for ‘‘reserved’’,
descriptive words (e.g., ‘‘fascinating’’, ‘‘cautious’’); how- and À1.19 for ‘‘boring’’ and ‘‘dull’’, since they are
ever, two nouns, ‘‘contrasts’’ and ‘‘alcoholism’’, were also synonyms) were multiplied by the number of their
included. occurrences and summed up. Response overall favorability
In the textual data, words belonging to the same value ¼ 1:97 þ 1:92 þ 0:08 þ ðÀ1:19Þ Ã 2 ¼ 1:59, i.e., favor-
synonymic group were replaced by the representative able. Responses that did not provide an answer to the
image variable using WORDER. All negative concepts question received a ‘‘zero’’ favorability value. The oper-
expressed in a multi-word format, such as ‘‘I would not feel ationalized ‘‘favorability’’ variable was of continuous data
safe’’ or ‘‘Russia is not well developed’’, were changed into type, its descriptive statistics are given in Table 5.
one-word format, that of ‘‘unsafe’’ and ‘‘undeveloped’’. Since the sample sizes to test the Hypothesis 1 were so
The evaluative descriptors obtained in the first part of the different (54 versus 283), the normality assumption for the
study were assessed on a ‘‘minus 2 to plus 2’’ positive– ‘‘favorability’’ variable was checked on the smaller sample,
negative scale by a group of US-born native English and the distribution was found to be normal (Kolmogor-
speakers, age 30 and above, not associated with the ov–Smirnov p ¼ 0.200, Shapiro–Wilk p ¼ 0.467). Test
respondents to Russia’s Destination Image online survey. results for the Hypothesis 1 are given in Table 6 and they
Forty-three evaluations were received. An a priori screen- were significant at the 0.1 level.
ing criterion for valid responses was ‘‘there should be no
positive response on the first ‘alcoholism’ variable’’; since a
positive response would indicate that a subject did not
Table 5
understand the task. Three responses were eliminated on
Favorability variable: descriptive statistics
this criterion. Two more were excluded because of four or
more missing entries, which might indicate a careless Variable N Minimum Maximum Mean SD
attitude to the evaluation process. Scores were examined
Favorability 337 À6.0832 8.7222 0.3267 2.2402
for internal consistency, and two outlier results were taken Valid N (listwise) 337
out. The values of every affective image variable were

Table 4
Affective image variables: frequencies and favorability scores

Variable Frequency Score Variable Frequency Score Variable Frequency Score

Friendly 85 1.92 Free 11 1.36 Alcoholism 6 À1.75
Somber 47 À0.39 Open 11 1.36 Hardworking 6 1.69
Depressing 45 À1.67 Interesting 11 1.61 Festive 5 1.78
Unfriendly 28 À1.64 Austere 11 À0.41 Contrasts 5 1.06
Cold 18 À0.31 Hostility 10 À1.44 Happy 5 1.83
Poor 18 À1.00 Unhappy 10 À1.56 Uncomfortable 5 À1.36
Reserved 17 0.08 Pleasant 10 1.58 Serene 4 1.53
Exciting 15 1.81 Difficult 9 À1.19 Safe 4 1.64
Tense 15 À1.11 Sad 8 À1.42 Hopeful 4 1.53
Unsafe 15 À1.78 Cosmopolitan 8 1.44 Ruthless 4 À1.53
Good 15 1.72 Cordial 8 1.56 Seedy 4 À1.28
Upbeat 14 1.43 Cautious 7 À0.33 Historical 4 1.67
Awesome 14 1.72 Boring 7 À1.19 Unpleasant 3 À1.68
Undeveloped 13 À0.58 Fascinating 7 1.97 Relaxing 2 1.47


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4.3. Research question 3: uniqueness images 4.4. Research questions 4 and 5: common destination
attributes
To find what unique places and features US pleasure
travelers associated with Russia, responses to question Q3 With respect to attribute-based items, this study
were analyzed. The CATPAC procedure on the pooled closely followed Echtner and Ritchie’s (1993) framework.
data was run, and 40 most frequent words indicating the Prior to analyzing the attribute-based items, eight nega-
unique Russian features were identified. Some words were tively formulated statements were re-coded in positive for
grouped together (e.g., ‘‘architecture’’ and ‘‘buildings’’) to the consistency of measurement and ease of results
reinforce concepts. As a result of the grouping process, the interpretation. In Table 8 the attributes are arranged from
final set of Russia’s uniqueness variables was produced. A most to least favorably assessed, based on the whole sample
table of synonyms was constructed and used as input for of responses. Attributes are considered positively or nega-
the WORDER program. Occurrences of every uniqueness tively assessed if their mean is below or above the neutral
variable were counted and entered into the SPSS database. ‘‘3.00’’ value, respectively. Hypothesis 1 test results are given
Responses like ‘‘do not know’’ were included into the in the last column of Table 8. As can be seen from the table,
frequency analyses as having ‘‘0’’ frequencies. As can be the past visitor group gave a more favorable assessment of
seen from Table 7, the list of unique Russian features is Russia’s destinath Varimax rotation was employed to reduce
nearly exhaustive. The group of past visitors displayed a the 44 destination attributes into nine factors. Ten attributes
better knowledge of unique Russian features. (nature preserves; nightlife/entertainment; costs/price levels;

Table 6
Favorability variable: visitors vs. non-visitors

Visitation N Mean Levene’s test for equality of variances t-Test for equality of means

F Significant t df p-Value

Visitors 54 0.808 3.572 0.060 1.726 335 0.085
Non-visitors 283 0.235

Table 7
Uniqueness images

# Unique features All respondents 336 Visitors n1 ¼ 54 Non-visitors n2 ¼ 283

Frequency Mean Frequency Mean Frequency Mean

1 St. Petersburg 113 0.34 25 0.46 88 0.31
2 Red Square 92 0.27 19 0.35 73 0.26
3 Kremlin 75 0.22 11 0.20 64 0.23
4 Moscow 73 0.22 23 0.43 50 0.18
5 Hermitage/winter palace 44 0.13 19 0.35 25 0.09
6 Churches/cathedrals 38 0.11 10 0.19 28 0.10
7 Museums 37 0.11 11 0.20 26 0.09
8 Art 35 0.10 11 0.20 24 0.08
9 Architecture 26 0.08 4 0.07 22 0.08
10 Czars (imperial Russia) 25 0.07 8 0.15 17 0.06
11 Palaces 22 0.07 9 0.17 13 0.05
12 Cruises 15 0.04 8 0.15 7 0.02
13 Summer palace 12 0.04 10 0.19 2 0.01
14 Siberia 11 0.03 3 0.06 8 0.03
15 Small towns 9 0.03 7 0.13 2 0.01
16 St. Basil’s cathedral 8 0.02 4 0.07 4 0.01
17 Lenin’s tomb 8 0.02 3 0.06 5 0.02
18 Onion-shaped domes 8 0.02 1 0.02 7 0.02
19 Black Sea 8 0.02 1 0.02 7 0.02
20 Trans-Sib 8 0.02 1 0.02 7 0.02
21 Volga River 8 0.02 1 0.02 7 0.02
22 Leningrad 4 0.01 1 0.02 3 0.01
23 Chernobyl 3 0.01 0 0.00 3 0.01
24 Baikal 3 0.01 1 0.02 2 0.01


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Table 8
Common destination attributes

Destination attributes N ¼ 336 Visitors n1 ¼ 54 Non-visitors n2 ¼ 283 t-Test

Mean SD Mean SD Mean SD p-Value

Sites/museums 1.64 0.76 1.20 0.49 1.72 0.78 0.000**
Architecture 1.65 0.71 1.43 0.79 1.70 0.69 0.010*
Customs/culture 1.77 0.63 1.67 0.67 1.79 0.62
Opportunity to learn 1.87 0.72 1.58 0.60 1.92 0.73 0.002**
Arts 1.87 0.71 1.48 0.64 1.95 0.70 0.000**
Scenery 2.01 0.83 1.83 0.84 2.05 0.82
Family or adult oriented 2.17 0.65 2.19 0.74 2.16 0.63
Non-capital Russia 2.18 0.76 1.91 0.73 2.23 0.75 0.004**
Cities 2.22 0.89 2.00 0.97 2.27 0.86 0.042*
Tourist attractions 2.28 0.94 1.69 0.77 2.40 0.93 0.000**
Cruises 2.32 0.75 1.98 0.76 2.38 0.73 0.000**
Combined trips 2.33 0.79 2.06 0.86 2.38 0.77 0.006**
Unique natural resources 2.33 0.82 2.31 0.95 2.33 0.80
Trans-Sib 2.38 0.68 2.41 0.71 2.37 0.68
Different cuisine 2.43 0.89 2.54 1.18 2.41 0.82
Hospitality/friendliness 2.45 0.85 2.06 0.92 2.52 0.81 0.000**
Nightlife 2.47 0.79 2.26 0.83 2.52 0.78 0.028*
Atmosphere 2.52 0.77 2.30 0.94 2.56 0.72
Tours/excursions 2.57 0.84 2.15 0.81 2.65 0.82 0.000**
Fairs/festivals 2.61 0.92 2.56 0.98 2.63 0.91
Knowledge of Russian History 2.64 0.97 2.09 0.52 2.75 1.00
Costs/price levels 2.65 0.81 2.19 0.93 2.74 0.76 0.000ÃÃ
Fishing/hunting 2.66 0.73 2.76 0.78 2.65 0.72
Life of people 2.69 0.79 2.76 0.93 2.68 0.76
Nature preserves 2.77 0.86 2.57 0.87 2.81 0.86
Fame/reputation 2.90 1.02 2.28 0.91 3.02 1.00 0.000ÃÃ
Quality food 2.93 0.85 2.70 1.11 2.98 0.78
Safety 2.98 0.87 2.78 0.86 3.02 0.87
Ease of communication 3.04 0.84 2.93 1.04 3.06 0.80
Quality of service 3.05 0.68 3.11 0.84 3.04 0.64
Opportunity for adventure 3.05 0.79 3.13 0.70 3.04 0.80
Sports activities 3.06 0.68 2.98 0.76 3.08 0.67
Restaurants 3.09 0.72 3.00 0.89 3.10 0.69
Rest and relaxation 3.15 0.73 3.09 0.93 3.16 0.69
Climate 3.20 0.89 2.69 0.82 3.30 0.88 0.000ÃÃ
Transportation 3.21 0.73 3.02 0.92 3.25 0.69 0.034Ã
Beaches 3.22 0.86 3.15 0.86 3.24 0.85
Accomodations 3.23 0.82 3.17 0.84 3.25 0.81
Cleanness 3.27 0.74 3.41 0.90 3.24 0.70
Shopping facilities 3.27 0.76 3.00 0.97 3.32 0.70 0.023Ã
Accessibility 3.35 0.78 3.28 1.15 3.36 0.69
Political stability 3.44 0.89 3.21 0.93 3.48 0.88 0.041Ã
Crowdedness 3.60 0.70 3.83 0.75 3.55 0.68 0.007ÃÃ
Economic development 3.84 0.71 3.87 0.73 3.83 0.71
Ã Significant at 0.05 level.
ÃÃSignificant at 0.01 level.

accessibility; climate; crowdedness; rest/relaxation; chance (Factor 3); Safety (Factor 4); History (Factor 5); Food
to see how people really live; atmosphere; and arts) had Culture (Factor 6); Service (Factor 7); Adventure
either low communalities or factor loadings and were taken (Factor 8), and Family/adult (Factor 9). Factor 9 consisted
out to improve the characteristics of the solution. The final of a single attribute; however, taking it out reduced the
KMO measure of sampling adequacy was 0.902; com- characteristics and interpretability of solution. The percen-
munalities ranged from 0.500 to 0.779; all factor loadings tage of variance explained as well as the high factor loading
were greater than 0.40. The total variance explained was justified retaining it. Cronbach’s alpha was adequate for all
61.05%. The results are given in Table 9. The factors were factors but Factor 8. All cross loadings made sense from
self-explanatory and were named as Traditional Tourism the solution interpretability point of view. For example,
(Factor 1); Infrastructure (Factor 2); Niche Tourism Scenery from Factor 1, Traditional Tourism, also loaded


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Table 9
Destination image factors

Factors F1 F2 F3 F4 F5 F6 F7 F8 F9
traditional infrastructure niche safety history food service adventure family
tourism tourism and culture adult

Variance explained 12.84 8.36 8.01 7.46 5.66 5.49 5.42 4.26 3.56
Eigenvalue 9.13 2.59 1.77 1.45 1.37 1.23 1.19 1.02 1.01
Cronbach’s alpha 0.86 0.74 0.77 0.73 0.62 0.62 0.58 0.48
Variables and communalities
Sites/museums 0.64 0.740
Architecture 0.58 0.700
Tourist attractions 0.65 0.693
Cities 0.69 0.692
Non-capital Russia 0.60 0.634
Opportunity to learn 0.61 0.610
Scenery 0.56 0.540 0.437
Hospitality 0.55 0.433
Transportation 0.57 0.681
Restaurants 0.63 0.616
Shopping facilities 0.58 0.576
Sports activities 0.57 0.575
Unique natural resources 0.66 0.689
Fishing/hunting 0.61 0.686
Cruises 0.59 0.526
Beaches 0.50 0.483
Trans-Sib 0.64 0.454 0.412
Political stability 0.64 0.763
Safety 0.63 0.692
Cleanness 0.53 0.601
Economics 0.57 0.434 0.457
Knowledge of Russian history 0.62 0.747
Fame/reputation 0.58 0.409 0.491
Combined trips 0.63 0.421 0.445 À0.426
Tours/excursions 0.54 0.442
Different cuisine 0.63 0.673
Customs/culture 0.64 0.616
Quality food 0.69 0.452 0.515
Quality of service 0.64 0.701
Accommodations 0.67 0.425 0.642
Fairs/festivals 0.55 0.638
Ease of communication 0.64 0.754
Opportunity for adventure 0.56 0.450
Family or adult oriented 0.78 0.855

on Factor 3, Niche Tourism, along with such items as Advertising and promotion of Russia to the interna-
Natural Resources, Fishing/Hunting, Cruises, Beaches, tional traveler has been very minimal in terms of financial
and Trans-Sib. resources in comparison to the efforts of other major
destinations. In 2003, prior to this research, the Russian
5. Discussion promotional budget on the federal level was USD 3.0
million (Izvestia, issue 01.21.05), which was two times
5.1. Implications for the FTA less than what was spent by Paris or Singapore alone.
The result of insufficient advertising has been a lack
Although Russia is one of the major world tourist of awareness about Russia’s tourist features as was
destinations (WTO, 2006b), it has not received enough indicated by the current study. The share of respondents
academic attention to date. Thus, this study partly fills the who put ‘‘don’t know’’ as the answer to the question
gap by assessing the country’s destination image among US Q3 about unique Russian features was 19%. The truly
pleasure travelers, one of the most affluent travel markets in unique Russian natural resources that are included in
the world. The implications of the study have relevance to the UNESCO World Heritage List, such as the Golden
the current FTA initiative to build a successful Brand Russia. Mountains of Altai, Volcanoes of Kamchatka, Virgin Komi


ARTICLE IN PRESS

Forests and others, were not mentioned at all. Lake Baikal Russia’s tourism attributes. The results indicated that
was mentioned by three people only. While a number of adequate promotional information is needed to correct the
respondents mentioned Russia’s countryside, small towns negative perceptions of non-visitors.
and villages, no specific names emerged. Several of Russia’s functional common attributes such as
With regard to the other two open-ended questions, economic development, accessibility, shopping facilities,
particularly about affective images, the problem was not cleanliness, accommodations, beaches, transportation,
that American pleasure travelers knew little about Russia. restaurants, and sports activities were ranked negatively
The survey respondents knew various things about the (mean score higher than 3.0) by the respondents (see
country, but their perceptions were often unfavorable. Out Table 8). Four of these items—transportation, restaurants,
of 42 affective image variables, 20 had negative favorability shopping facilities, and sport activities—made up a
scores, and out of 337 responses, 129 and 59 had negative separate Infrastructure factor, and two more items—
and zero favorability values, respectively. The ‘‘Soviet era’’ economic development and accommodations—had load-
image still lingered. Poor people, country, lodgings, and ings greater than 0.40 on this factor (see Table 9). This
food choices were often present in the responses to Q1 indicated that the level of infrastructure is a consideration
about the stereotypical images. ‘‘Poor’’, ‘‘undeveloped’’, for US pleasure travelers in the process of destination
‘‘hostile towards Americans’’, ‘‘ruthless’’, ‘‘depressing’’, selection. Therefore, promotion of tourism types that are
and ‘‘unsafe’’ country emerged from about half of less sensitive to levels of infrastructure development is
responses to Q2. Such attributes of the Soviet era, as the advisable, since they potentially have a higher probability
Cold War, Lenin’s tomb, Stalin, and Leningrad, were also of success (Ilyina Mieczkowski, 1992). These tourism
mentioned. types are also less sensitive to the service levels, with service
The survey respondents did not agree whether Russian being another important consideration for potential
people were friendly or not, which was registered in their travelers.
answers to both Q1 and Q2. Respondents who thought As this study indicated, ‘‘traditional tourism’’ has the
Russian people to be friendly often added such descriptors strongest position image-wise in the minds of US pleasure
as ‘‘somber’’ and ‘‘reserved’’. These attitudes can be travelers (see Table 9). Historical sites and museums,
partially explained by the age of the respondents, more capital and provincial cities rich in architecture and
than 70% of whom were more than 55 years old. Another cultural heritage, beautiful scenery, and opportunities to
possible explanation is the complicated procedure of interact with Russian people should be combined in an
obtaining a Russian visa. The lack of positive materials attractive package. Up-to-date information on the safety
about Russia in the US general media also plays a role in and hygiene conditions, as well as infrastructure levels,
American pleasure travelers’ negative perceptions of the should be effectively communicated. Another possibility is
country. The attribute-based ‘‘hospitality-friendliness’’ the Trans-Siberian journey with stopovers in unique nature
item indicated that visitors thought Russian people were preserves and cultural and historical locations. The levels
friendlier (mean 2.06) than non-visitors (mean 2.52). of comfort, service, and infrastructure of such a trip are
However, the ‘‘hospitality-friendliness’’ perceptions of high for the first- and second-class ticket holders. Given the
non-visitors are very important for the FTA, since they average age of the ATC members, they might not be the
might interfere with the desire to go Russia. No country audience for adventure or eco-tourism travel offers.
that wants to develop a strong tourism sector can afford to Hypothesis 1 addresses the relationship between image
be perceived as unfriendly to visitors. The branding and visitation. As indicated in Section 2.1, the nature of
approach might be the answer to this problem, since the this relationship is complex and multi-faceted. The act of
visitor’s satisfaction is in large part a matter of expectations visiting a destination can certainly change the image one
(Chon, 1990). Careful branding of the Russian nation as has of that destination. This can best be examined in terms
the reserved people who are cordial to guests and open and of pre- and post-visitation images, which were not available
warm to friends might be successful. To reinforce the in this study. In turn, the favorability of a destination’s
politeness/cordial perception, extensive human resources image can influence whether one chooses to visit the
training programs in the hospitality and tourism sector destination in the first place. Therefore, association between
are also of primary importance and should be initiated by image and visitation is a two-way cause–effect relationship.
the FTA. However, the authors feel that, from a marketing stand-
With regard to functional attributes, significant differ- point, the direction of the relationship is not as important
ences were registered for 19 items with visitors giving more as the existing ‘‘image-visitation’’ association itself. ‘‘The
favorable assessments. This is a very interesting finding for more favorable the image is, the more likely visitation will
the FTA because it suggests that quality of Russia’s tourist occur’’ direction stresses the need for adequate advertising
offer is, in fact, better than the non-visitors think it is. of Russia in the US travel market. The ‘‘destination image
Given that no significant differences were registered changes as a result of actual visitation’’ direction implies
between visitors and non-visitors in terms of demographic that with regard to this study, the actual Russian offer
characteristics, the differences in evaluations can be (assessed by the past visitors) is better than the perceived
attributed to the differences in the actual and perceived one (assessed by non-visitors), which again highlights the


ARTICLE IN PRESS

necessity of adequate marketing communications to various 5.3. Limitations and further research
groups of potential first- and repeat visitors.
The study confirmed that the parsimonious set of 35
scale items on common destination attributes proposed by
5.2. Generalizability of results Echtner and Ritchie (1993) can be successfully used for a
very broad range of destinations, including such large and
Generalizability of the results was a concern in this diverse countries as Russia. Factor analysis conducted on a
study. Does the obtained sample of ATC members truly 35-item set resulted in seven factors, the interpretation of
represent American leisure travelers? To examine this which had much in common with the factors obtained by
question, three comparisons were made: (1) between ATC Echtner and Ritchie (1993). Adding Russia-specific attri-
members and US pleasure travelers to Europe; (2) between butes made the factor solution less stable, and 10 attributes
population under study (ATC members with Internet had to be taken out. The resulting factors were essentially
access) and the whole ATC membership; and (3) between the same with one notable exception: Russia-related
the obtained sample and the population under study. First, attributes mostly fell into the Niche Tourism factor. This
to answer how well ATC members represent the entire suggests that including new, destination-specific attributes,
population of US long-haul tourists, the entire ATC into a set of well established attributes should undergo a
membership profile (Morrison, So, Beldona, Feng, rigorous selection procedure, similar to that which was
Stepchenkova, 2004) was qualitatively compared to the employed by Echtner and Ritchie (1993).
profile of a typical US traveler to Europe (European Travel Russia as a tourist destination does not equal Russia as a
Commission (ETC), 2001). US outbound pleasure travelers country. Kotler and Gertner (2002, p. 251) pointed out that
tend to be more highly educated than the US adult ‘‘a country’s image results from its geography, history,
population as a whole and wait until they are older to do proclamations, art and music, famous citizens and other
the bulk of their international long-haul travel. Addition- features’’. Destination and country images are overlapping
ally, travelers to Europe are more affluent than the average constructs (Mossberg Kleppe, 2005), and Russia’s
US outbound traveler, and three-quarters of them travel as destination image is undoubtedly influenced by the
couples. The proportion of younger members in the ATC is country’s image, however, it is not clear to what degree.
twice as small as that of American travelers to Europe; Therefore, it is important to assess how Russia’s destina-
therefore, it was concluded that ATC members were tion image is affected by the often negative coverage of
representative of the older US pleasure travelers Russia as a political entity in the US general media. The
group. Second, the sample of ATC members obtained in question as to whether these two images can be separated
this study was compared to the overall ATC membership in the minds of potential travelers to Russia has direct
profile. Significant differences were found for the ‘‘age’’, relevance to successful building of Brand Russia.
‘‘education’’, and ‘‘job’’ variables. Respondents of this This study dealt with the image of Russia as a travel
study were older and more educated, and had a larger destination among US pleasure travelers. However, the US
share of professionals and retirees. This finding was is only one potential market for Russia’s inbound tourism.
somewhat expected, since the population of this study The large distance between the two countries might have a
was limited to ATC members with Internet access. While negative effect on how Russia is perceived by US travelers
the comparison suggested that the study sample was as suggested by Reilly (1990). Other, geographically closer
not representative of the entire ATC membership, the markets might be better suited for focused promotional
profile of the respondents did correspond to that of efforts of the FTA, because they might already possess a
the older, affluent, and well-educated US pleasure travelers more favorable and accurate image of Russia that would
to Europe. Finally, the low overall response rate ($7%) require less effort and finance to enhance and positively
did not allow conclusion that the opinions of people induce.
who participated in the survey were representative of the
entire population under study (ATC members with
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