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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,�

aDepartment of Hospitality and Tourism Management, Purdue University, 154 Stone Hall, 700 W. State Street, West Lafayette, IN 47907-2059, USAbDepartment 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

Russia is a vast country with rich tourist resources of allkinds. They include unique natural features, beautifullandscapes, historical and cultural attractions, places ofethnographic interest, and good recreational opportunities.However, while Russian outbound and internal tourismhave been growing rapidly, inbound tourism is growingslowly and for the several years has been suffering frompolitical instability associated with terrorist activity inRussia; therefore, income from international tourism is asmall share of Russia’s overall economy (Russia’s StateStatistics Service (Rosstat), 2006). Since the 1990s, Russiahas been successfully developing its tourist offer; never-theless, some problems still remain. Among the factors thatprevent faster growth of Russia’s inbound tourism are alack of infrastructure, especially in the country’s eastern

e front matter r 2007 Published by Elsevier Ltd.

urman.2007.06.003

ing author. Tel.: +1765 494 7905; fax: +1 765 496 1168.

esses: [email protected] (S. Stepchenkova),

e.edu (A.M. Morrison).

s article as: Stepchenkova, S., & Morrison, A. M. Russia’s de

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

areas, complicated visa procedures, rising prices for tourpackages, and lack of advertising. To realize its tourismpotential, the country needs not only to solve the above-mentioned problems but also to attractively present itselfto international travelers. To become a competitive globaldestination, the Federal Tourism Agency of RussianFederation (FTA) needs to develop Brand Russia whichwould firmly position the country among the competitivedestinations of Eastern Europe and Asia. Given the size ofthe US tourist market and the fact that US pleasuretravelers are the world’s leading travel spenders (WTO,2006a), this segment is very attractive for the Russiantourism industry from an economic standpoint.To be successfully promoted in a particular market, ‘‘a

destination must be favorably differentiated from itscompetition, or positively positioned, in the minds of theconsumers’’ (Echtner & Ritchie, 2003, p. 37). A desirabledifferentiation and positioning can be achieved by adestination’s marketing organization by creating andmanaging the perceptions, or images, that potentialtravelers hold about the destination. Therefore, the purpose

stination image among American pleasure travelers: Revisiting Echtner

www.elsevier.com/locate/tourman

dx.doi.org/10.1016/j.tourman.2007.06.003

mailto:[email protected]

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ARTICLE IN PRESSS. Stepchenkova, A.M. Morrison / Tourism Management ] (]]]]) ]]]–]]]2

of this study was to examine Russia’s destination imageamong US pleasure travelers by investigating the followingquestions:

1.

P

a

What stereotypical holistic images do US pleasuretravelers associate with Russia?

2.
What affective images does Russia as a travel destina-tion evoke?
3.
What unique places and features do US pleasuretravelers associate with Russia?
4.
What are US pleasure travelers’ perceptions of Russia’sdestination attributes?
5.
Does the degree of familiarity with Russia (visitors/non-visitors) affect the destination image of Russia?
The lack of information is evident: a destination imageliterature review conducted by Pike (2002) for the period of1973–2000 found that only one out of 142 articles had dealtwith Russia’s image, and this study by Pizam, Jafari, andMilman (1991) reflected the old, ‘‘Soviet’’ image of thecountry. The analysis of Russia’s destination image as heldby US pleasure travelers should be useful to both the FTAand Russian travel providers, to see how Russia isperceived by one of the largest tourist markets in theworld, and to counter negative or inaccurate perceptions ofpotential visitors.

2. Study background

2.1. Destination image construct

The concept of ‘‘image’’ that has been studied for severaldecades in such disciplines as social and environmentalpsychology, marketing, and consumer behavior, wasintroduced into tourism studies in the early 1970s by Hunt(1971), Mayo (1973), and Gunn (1972) and has sincebecome one of the most researched topics in the field.However, as meta-analyses of destination image studiesindicated (Chon, 1990; Gallarza, Saura, & Garcia, 2002;White, 2004), due to its complexity, subjectivity, andelusive nature, the concept of destination image has beeninterpreted differently by various researchers. The view ondestination image as an overall impression is rooted inpsychological tradition and consumer behavior theory(Assael, 1984; Herzog, 1963) and was supported by Hunt(1971) and Reilly (1990). However, operationalization ofthe destination image construct without breaking it intoseparate, more evaluative elements is problematic. Tourismscholars generally agree that destination image holds atleast two distinctive components—cognitive and affective(Baloglu & Brinberg, 1997; Baloglu & McCleary, 1999).The cognitive, or perceptual, element refers to knowledgeand beliefs about a destination, while the affective elementrefers to feelings about a destination.

Despite the composite nature of the destination imageconstruct, in most destination image studies researchershave emphasized the cognitive dimension (Pike & Ryan,

lease cite this article as: Stepchenkova, S., & Morrison, A. M. Russia’s de

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

2004). Strong support for cognitive interpretation of imageas a set of relevant attributes is given by Gensch (1978):‘‘Products seldom are measured or evaluated as single lumpsum entities; rather, it is the attributes of the alternativesthat are measured, compared, and form the basis forchoice’’ (cited in Gartner, 1986, p. 636). This view wasfurther supported by Engel, Blackwell, and Miniard (1986),who stated that image is the consumer’s subjectiveperceptions, which refer to how an alternative performson important evaluative criteria.Social and environmental psychological tradition re-

gards cognition and affect as interrelated elements, whereaffect is largely dependent on cognition (references to thisview can be found in Baloglu & McCleary, 1999).However, Russell and Snodgrass (1987, p. 246) arguedthat ‘‘behavior may be influenced by the (estimated,perceived, or remembered) affective quality of an environ-ment rather than by its objective properties directly’’. Theaffective component of destination image expresses feelingstoward a destination, which can be favorable, unfavorable,or neutral. Gartner (1993) suggested that the affectivecomponent comes into play at the stage when differenttravel alternatives are evaluated. Furthermore, there arerecent indications that emotions might be better predictorsof behavior than perceptual evaluations (Yu & Dean,2001). Despite its obvious importance, affect has generallybeen overlooked by destination image researchers: only sixout of 142 studies surveyed by Pike (2002) studied affectiveimages.Gartner (1993), Pike and Ryan (2004), and White (2004)

among other scholars, also recognized a third—conative orbehavioral—element in the destination image construct,which is related to how travelers act toward a destinationon the basis of the cognition and affect they have about it.Conation reflects a likelihood of destination selection, orbrand purchase, and can be interpreted as a propensity tovisit a destination within a certain time frame (Pike &Ryan, 2004). The conative element of destination image isinfluenced by both the cognitive and affective components.Familiarity plays an important role in destination image

formation. It influences destination perceptions andattractiveness and represents a key marketing variable insegmenting and targeting potential visitors (Baloglu, 2001).Familiarity can be understood as previous experience witha destination (experience dimension) and knowledge aboutit (informational dimension). One stream of research onfamiliarity and destination image compares pre- and post-visitation destination images. Phelps (1986) recognizedsecondary destination images, as formed by travelers’exposure to different information sources, and primaryimages, which are created after actual visitation. Herresearch, as well as the studies done by Pearce (1982), Chon(1991), and Dann (1996), suggested that visitation affectsimages and changes some of the perceptions about adestination. Post-visitor perceptions were found to be morepositive than those of pre-visitors. However, there areindications that a relationship between visitation and



ARTICLE IN PRESSS. Stepchenkova, A.M. Morrison / Tourism Management ] (]]]]) ]]]–]]] 3

destination images is more complicated. Pizam et al. (1991)studied pre- and post-images of a group of US students whovisited the Soviet Union, and found that, basically, theimages stayed the same. The other stream of researchdetermined how destination images differed between visitorsand non-visitors (Ahmed, 1991; Chon, 1991; Milman &Pizam, 1995) or non-visitors, first-timers and repeat visitors(Fakeye & Crompton, 1991). Images of visitors tend to bemore favorable; however, no significant differences werefound between perceptions of first-time and repeat visitors.This suggested that most changes in destination image occurduring the first visitation. Therefore Hypothesis 1 wasformulated to answer research question 5:

Hypothesis 1. ‘‘US residents who have visited Russia havemore favorable images of the destination than those whohave not’’.

2.2. Conceptualization by Echtner and Ritchie (1991)

In the whole body of destination image studies, Echtnerand Ritchie (1991, p. 11) proposed a somewhat uniqueconceptualization of the destination image construct basedon an extensive review of the literature on destinationimage research for the period of 1975–1990:

�

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‘‘Destination image should be envisioned as consistingof two main components; those that are attribute-basedand those that are holistic.
� Each of these components of destination image contains
functional, or more tangible, and psychological, or moreabstract, characteristics.
� Images of destinations can also range from those based
on ‘‘common’’ functional and psychological traits tothose based on more distinctive or even unique features,events, feelings or auras’’.

The attribute-based component is captured by a series ofscale items that range from tangible, or functional(beaches, shops, sports facilities, etc.), to more intangible,or psychological (receptiveness of local people, quality ofservice, etc.). These attributes also represent a commondimension of a destination, since every destination can beevaluated on the basis of these general criteria. The holisticcomponent is captured by two open-ended items (Echtner& Ritchie, 1991, p. 11):

�
‘‘What images or characteristics come to mind when youthink of _______ as a travel destination? � How would you describe the atmosphere or mood that
you would expect to experience while visiting _______?’’

The first question is functional, while the second one ismore psychologically oriented. Responses to the seconditem include affective evaluations, such as exciting,relaxing, boring, etc., and, therefore, resemble the Balogluand Brinberg (1997) affective component (White, 2004).

lease cite this article as: Stepchenkova, S., & Morrison, A. M. Russia’s de

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

Altogether, the holistic component is positioned as amental picture, or overall representation, of the destina-tion, and, as such, resembles the overall component of thedestination image. The holistic component is important forunderstanding how a particular destination is categorizedin the minds of consumers, and what prevailing images andstereotypes are associated with a given destination. In thefollowing sections of this article, images derived from theanswers to these two questions are referred to as‘‘stereotypical’’ and ‘‘affective’’, respectively. The unique-ness dimension is assessed by the item:

�
‘‘Please list any distinctive or unique tourist attractionsthat you can think of in _______’’.
This component is very important for differentiating adestination from a competitive set of destinations, and willbe further referred to as the ‘‘uniqueness image’’.Thus, Echtner’s and Ritchie’s approach lies within the

cognitive-affective-overall image tradition and is consistentwith MacKay’s and Fesenmaier’s (1997, p. 538) view that‘‘a destination image is a composite of various products(attractions) and attributes woven into a total impression’’.Echtner and Ritchie (1993) suggested a conceptual frame-work for operationalization of all specified components ofdestination image, as well as proposed a convenientformat for visual representation of image components. Indesigning the scale for measuring the attribute-baseditems, Echtner and Ritchie followed the frameworkproposed by Churchill (1979) for marketing studies. Stepssuch as specifying the domain of the image construct,generating a sample of items, purifying the measures usingCronbach’s alpha as an indicator, and iterative factoranalysis were conducted. Thus, the issues of contentvalidity, dimensionality, and internal consistency reliability(Peter, 1979) of the proposed scale were addressed by theresearchers.

3. Methodology

3.1. Destination image measurement

The composite nature of the destination image constructpresents great challenges for its measurement. Strongpreference has been given to structured methods whendata were obtained as answers to close-ended surveyquestions (Pike, 2002). While structured methodologieshave a number of advantages over qualitative methods,they focus on particular destination attributes and gen-erally neglect the holistic aspect of destination image.Qualitative studies, on the contrary, are helpful inmeasuring the holistic aspect, but do not facilitatestatistical and comparative analyses of destination images(Jenkins, 1999). Echtner and Ritchie’s (1993) methodologyframework provided a much needed balance betweenquantitative and qualitative aspects of image measurement.




This research closely followed the methodology suggestedby Echtner and Ritchie (1993) with regard to thequantitative analysis of the destination image, and tooktheir approach a step further with respect to the qualitativeimage assessment. It is not the purpose of this study toprovide an extended literature review of the qualitativemethods that have been employed in the analysis ofdestination images—an extensive overview can be foundin Ryan and Cave (2005). However, it should be noted thatcontent analysis of textual and/or pictorial materials byReilly (1990), Echtner and Ritchie (1993), Dann (1996),MacKay and Fesenmaier (1997), Andsager and Drzewiecka(2002), Echtner (2002), and Ryan and Cave (2005), amongothers, employed sorting and categorization techniques toidentify the frequencies of certain words, concepts, objects,or people, and treated the most frequent ones as imagevariables. The final set of image variables can containnouns, verbs, and descriptors (i.e., adjectives and adverbs),since nouns are used to focus attention on attractions (e.g.,museums, Lake Baikal), verbs describe actions or tourismtypes (e.g., rafting, sightseeing), and descriptors (e.g.,ancient, exciting) create atmosphere (Echtner, 2002). Theanalysis can be computer-assisted (e.g., Ryan & Cave, 2005)or done by hand, and identified image variables are thenoften placed on a plane or a line along specified dimensionsto provide image visualization (Echtner & Ritchie, 1993).

The large volume of textual data in qualitative studiesand the repetitiveness of the task made the computer anatural and powerful choice for content analysis despitethe fact that not all nuances of the language can berecognized by any given software program (Alexa & Zuell,2000). For content analysis of open-ended questions, thisstudy used a combination of two software programs,CATPAC (Woelfel, 1998) and WORDER (Kirilenko,2004) in order to answer research questions 1, 2, 3 and 5and test Hypothesis 1 not only on attribute-based items buton textual responses as well. CATPAC has been employedfor more than a decade in content analysis of politicalspeeches, focus group interviews, marketing studies, anddestination images to ‘‘identify the most important wordsin a text and determine patterns of similarity based on theway they are used in text’’ (Woelfel, 1998, p. 11) and alsobecause of its strong visualization capabilities. However,CATPAC analyzes only one textual file at a time.WORDER software was developed to process in one runup to 1000 files of similar type (e.g., survey responses,newspaper articles, etc.) and count the number of specifiedkey words/image variables in every one of them. Ultimately,the approach used in this study allows: (1) identificationof destination image variables in digital textual data usingCATPAC, and (2) counting the occurrences of thesevariables in every textual survey response with WORDER.The result is a two-dimensional data matrix, which can beeasily transferred into any statistical package for furtherstatistical analysis and clustering purposes.

Normally, a laborious ‘‘smoothing out’’ procedureshould be performed on the textual data prior to analysis:

Please cite this article as: Stepchenkova, S., & Morrison, A. M. Russia’s de

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

misspellings, synonyms, and multi-word concepts have tobe taken into account (Woelfel, 1998); however, the necessarychanges should concern only the meaningful words, or imagevariables in our case. WORDER has a built-in function thatallows making changes in the data by means of the inputtable, simultaneously with the counting process. The detailsof the CATPAC-WORDER approach can be found inStepchenkova, Kirilenko, and Morrison (2006).The computer-assisted approach employed in this study

for content analysis of textual responses to three imagequestions (stereotypical, affective, and uniqueness) providesa more detailed assessment of destination image andfacilitates statistical comparisons of images among differentgroups of respondents, thus enriching the destination imagemeasurement methodology proposed by Echtner andRitchie (1993). The application of CATPAC-WORDERsoftware combination discussed above and a way tocompare favorability of affective images in order to testHypothesis 1 discussed in Section 4.2 is considered acontribution of this study from the methodology standpoint.

3.2. Research instrument

The original questionnaire (Echtner, 1991), with two itemsfor each of 35 attributes, was obtained. It was decided to useonly one item per attribute for this study. Two attributes,namely, degree of urbanization and extent of commercializa-tion were thought to be better applicable to small destinationsand were excluded. An accommodation/restaurants attributewas split into two separate items, since accommodationshortage is a known problem for the Russian tourist sector,but the situation is much better with restaurants.Prior to this research, the authors conducted two

exploratory studies to gain insights into induced andorganic aspects of Russia’s destination image (Stepchen-kova, Chen, & Morrison, 2007; Stepchenkova & Morrison,2006). In addition, five travel professionals and seven‘ordinary’ people were asked to provide answers to thethree Echtner’s and Ritchie’s open-ended questions onRussia’s image. As a result of these prior efforts, sevenRussia-specific attributes (cruises, combined trips, non-capital Russia, fishing and hunting, unique naturalresources, Trans-Siberian railroad, and arts) were addedto the questionnaire. Three general attributes—namely,good quality food, chance to see how people really live, andknowing something of a country’s history—were alsoincluded in the survey with the phrasing taking fromCrompton (1977) for a research purpose which is notexplained in this article due to a space constraint. Toensure clarity of the survey instrument, the phrasing ofattribute items was borrowed, when possible, from Echtner(1991) and tested in July 2005 by a group of graduatestudents from a large Midwestern university.

3.3. Population and data collection

The survey population came from one of the America’soldest and largest private travel clubs (further referenced as




ATC), serving tens of thousands of families in many states(�75 000 members, 30 000 households, predominantly inthe Midwest) at the time when the study was conducted.ATC members with Internet access (about 20 000) were thesample frame for this research, and a random sample of5000 e-mail addresses was selected from the ATC database.These people were sent an e-mail from the ATC manage-ment team with the request to take part in the study.The data were collected during three weeks in July–August2005. One hundred and eighty-nine responses wereobtained in the first round. A follow-up letter was senta week later, and 148 responses were collected in thesecond round. There were no differences between the 1stand 2nd round respondents for all the demographicvariables, except income. The aggregated profile of therespondents is given in Table 1. The total number ofRussia’s Destination Image Survey Website hits was503, the total number of submitted responses was 341,the number of usable responses was 337. These IPaddresses were checked to ensure that there were nodouble entries.

Table 1

Respondents’ profile

Variable Levels Whole sample

Frequency %

Visitation Visitors 54 16.0

Non-visitors 283 84.0

Total 337 100.0

Friends and/ Yes 31 9.2

or relatives No 306 90.8

in Russia Total 337 100.0

Gender Male 147 44.0

Female 187 56.0

Total 334 100.0

Education High school 19 5.6

Some college 53 15.7

Associate 24 7.1

Bachelor 105 31.2

Master 93 27.6

Ph.D. 40 11.9

PNTAa 3 0.9

Total 337 100.0

Job Administrative 20 5.9

Educator 21 6.2

Executive 21 6.2

Managerial 20 5.9

Professional 87 25.8

Sales/marketing 14 4.2

Self-employed 24 7.1

Student 1 0.3

Retired 111 32.9

Other 15 4.5

PNTA 3 0.9

Total 337 100.0

aPNTA—prefer not to answer.



Overall, the open-ended questions produced fewerresponses than the attribute statements: question Q1 aboutstereotypical image (What images or characteristics cometo mind when you think of Russia as a travel destina-tion?)—316; question Q2 about affective image (Howwould you describe the atmosphere or mood that youwould expect to experience while visiting Russia?)—313;and question Q3 about uniqueness image (Please listany distinctive or unique tourist attractions that youcan think of in Russia.)—273. Eleven respondentschose to give the same answers to questions Q1 and Q2or Q1 and Q3, putting in the answer field ‘‘See above’’,‘‘Same as #1’’, or ‘‘See #1’’, and substitutions were made asindicated. A certain percentage of respondents chose not tosubmit some of the demographic data; predictably, thehighest number of refusals was for the income question(14.6%). There were a number of responses that containedmissing values for one or a few attributes; however, thenumber of missing entries was small relative to thesample size, and the responses with missing entries werekept in the data.

Variable Levels Whole sample

Frequency %

Age 18–24 1 0.3

25–34 8 2.4

35–44 29 8.6

45–54 74 22.0

55–64 130 38.6

65 and older 86 25.5

PNTA 9 2.6

Total 336 99.7

Marital Single 47 13.9

status Married 252 74.8

With a partner 4 1.2

Widowed 27 8.0

PNTA 7 2.1

Total 337 100.0

Income Less than $30 000 6 1.8

$30 000–$49 999 24 7.1

$50 000–$74 999 48 14.2

$75 000–$99 999 58 17.2

$100 000–$149 999 81 24.0

$150 000–$199 999 31 9.2

$200 000 and above 41 12.2

PNTA 48 14.2

Total 337 100.0



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Table 3

Stereotypical holistic images

# Stereotypical holistic images

1 Cold weather, snow

2 Beautiful architecture and old buildings

3 Poor people, country, lodgings, and food choices

4 Historic sites and places

5 Moscow, Red Square, and Kremlin

6 St. Petersburg, Hermitage, palaces, and museums

7 Vast country with lots of open spaces

8 Beautiful countryside

9 Orthodox churches with onion-shaped domes

10 Big cities, interesting old cities

11 Great culture, different culture

12 Beautiful music, ballet, art

13 Friendly/unfriendly people

14 Volga River

15 Vodka

S. Stepchenkova, A.M. Morrison / Tourism Management ] (]]]]) ]]]–]]]6

4. Results

4.1. Research question 1: stereotypical holistic images

By following the CATPAC-WORDER procedure de-scribed in the previous section, a list of 72 most frequentmeaningful words was obtained using CATPAC. Somewords, e.g., ‘‘history’’, ‘‘historic’’, ‘‘historical’’ or ‘‘large’’,‘‘big’’, were grouped together under the most frequentname, in this case ‘‘history’’ and ‘‘large’’, to reinforceconcepts, and substitutions in the data were made byWORDER. Second, the frequencies of every specifiedstereotypical image variable were counted in every responseusing WORDER. Table 2 contains overall frequencies ofRussia’s stereotypical image variables.

The next step was to reduce the number of stereotypicalimage variables to a smaller number of image concepts bymeans of factor analysis. The dataset, which was obtainedby WORDER, had 45 variables and 317 cases, which gavea solid case to variable ratio of 7.04 (Kline, 1994). PrincipalComponents Analysis with Varimax rotation was used.Since textual responses were generally very short, e.g.,‘‘Cold. Beautiful churches’’, it was decided to look forstable word combinations, which might include as few astwo words, rather than for full 3–5 word factors. There-fore, the number of factors was not specified and theoption ‘‘Eigenvalues larger than 1’’ was chosen. Weakitems (‘‘dark’’, ‘‘interesting’’, and ‘‘exotic’’) with lowcoefficients in the diagonal of the anti-image matrix(o0.40), low communalities (o0.50) and those that didnot load higher than 0.35 on any factor were eliminated(Kline, 1994). The remaining variables produced 17 factorsthat explained 67% of the total variance.

The factor solution produced was an intermediate step toidentify the final stereotypical holistic images. Guided bythis solution, the factors were checked against the originaldata in order to ensure that word combinations containingdescriptive items such as cold, beautiful, poor, old, large,great, vast, friendly, different, were not used in a negativecontext, which would entirely change interpretability of the

Table 2

Stereotypical image variables

Variable Frequency Variable Frequency

Cold 69 Kremlin 24

Beautiful 55 Palaces 23

People 54 Weather 19

History 45 Museums 19

Buildings 39 Churches 19

Poor 38 Cities 18

Architecture 37 Large 15

Red Square 36 Interesting 13

St. Petersburg 34 Onion 13

Moscow 30 Art 13

Country 28 Great 12

Old 25 Vast 12



factors. The factor ‘‘great food’’ was eliminated as theresult of this check and due to a low reliability alpha.Another concern was that the stable word combinationsproduced by factor analysis did not account for largedifferences in frequencies between words combined in someof the image factors, e.g., in Factor 9, the word ‘‘old’’ had afrequency of 25, while the ‘‘buildings’’ word’s frequencywas 39. It meant that at least 14 occurrences of the word‘‘buildings’’ were used in other word combinations.Therefore, factors, which contained words with largedifferences in frequencies, were checked against the originaldata as well. As a result, some high frequency words, e.g.,‘‘poor’’, were associated with such words as ‘‘lodgings/accommodations’’, which were not originally included intothe stereotypical image variables set. Finally, some imagefactors were combined together, since they belonged to thesame image concepts, e.g., Factors 4 and 8 made oneholistic image of ‘‘orthodox churches with onion-shapeddomes’’, which was used in many responses. The finalresults of Russia’s stereotypical holistic images are given inTable 3.

Variable Frequency Variable Frequency

Food 12 Orthodox 7

Culture 12 Open 7

Friendly 12 Vodka 6

Domes 10 Exotic 6

Countryside 10 Sites 6

Snow 9 Volga 5

Hermitage 9 River 5

Music 9 Spaces 5

Winter 9 Ballet 5

Dark 8

Different 8

Places 7



ARTICLE IN PRESS

Table 5

Favorability variable: descriptive statistics

Variable N Minimum Maximum Mean SD

Favorability 337 �6.0832 8.7222 0.3267 2.2402

Valid N (listwise) 337

S. Stepchenkova, A.M. Morrison / Tourism Management ] (]]]]) ]]]–]]] 7

4.2. Research questions 2 and 5: affective images and

favorability analysis

To get insights into Russia’ affective images, the 337textual responses to question Q2 were evaluated forfavorability in order to test Hypothesis 1 not only forattribute-based items but on the textual responses aswell. Using CATPAC, the study identified all evaluativedescriptors (around 240) in the textual data providedby respondents, and combined them into 42 groups bysynonymous meanings, as suggested by thesauri, context,and expert opinions. One word for each group, usually themost frequent one, was selected as an affective imagevariable. The final set of image variables contained mostlydescriptive words (e.g., ‘‘fascinating’’, ‘‘cautious’’); how-ever, two nouns, ‘‘contrasts’’ and ‘‘alcoholism’’, were alsoincluded.

In the textual data, words belonging to the samesynonymic group were replaced by the representativeimage variable using WORDER. All negative conceptsexpressed in a multi-word format, such as ‘‘I would not feelsafe’’ or ‘‘Russia is not well developed’’, were changed intoone-word format, that of ‘‘unsafe’’ and ‘‘undeveloped’’.The evaluative descriptors obtained in the first part of thestudy were assessed on a ‘‘minus 2 to plus 2’’ positive–negative scale by a group of US-born native Englishspeakers, age 30 and above, not associated with therespondents to Russia’s Destination Image online survey.Forty-three evaluations were received. An a priori screen-ing criterion for valid responses was ‘‘there should be nopositive response on the first ‘alcoholism’ variable’’; since apositive response would indicate that a subject did notunderstand the task. Three responses were eliminated onthis criterion. Two more were excluded because of four ormore missing entries, which might indicate a carelessattitude to the evaluation process. Scores were examinedfor internal consistency, and two outlier results were takenout. The values of every affective image variable were

Table 4

Affective image variables: frequencies and favorability scores

Variable Frequency Score Variable Freq

Friendly 85 1.92 Free 11

Somber 47 �0.39 Open 11

Depressing 45 �1.67 Interesting 11

Unfriendly 28 �1.64 Austere 11

Cold 18 �0.31 Hostility 10

Poor 18 �1.00 Unhappy 10

Reserved 17 0.08 Pleasant 10

Exciting 15 1.81 Difficult 9

Tense 15 �1.11 Sad 8

Unsafe 15 �1.78 Cosmopolitan 8

Good 15 1.72 Cordial 8

Upbeat 14 1.43 Cautious 7

Awesome 14 1.72 Boring 7

Undeveloped 13 �0.58 Fascinating 7



averaged across the 36 remaining responses (Cronbach’salpha 0.786). The frequencies of each image variable werecounted by WORDER in every one of 337 textual files, andthe ‘‘favorability’’ values were computed for every responseby simply adding together all occurrences of positive andnegative image variables multiplied by their score. Thefrequencies of all affective image variables along with theirfavorability scores are given in Table 4.To calculate the favorability value for the response:

‘‘Fascinating country. Overall, people are friendly butreserved. Boring nightlife, dull food, though’’, the follow-ing procedure was implemented. The averaged favorabilityscores for all affective image variables in the response (1.97for ‘‘fascinating’’, 1.92 for ‘‘friendly’’, 0.08 for ‘‘reserved’’,and �1.19 for ‘‘boring’’ and ‘‘dull’’, since they aresynonyms) were multiplied by the number of theiroccurrences and summed up. Response overall favorabilityvalue ¼ 1:97þ 1:92þ 0:08þ ð�1:19Þ � 2 ¼ 1:59, i.e., favor-able. Responses that did not provide an answer to thequestion received a ‘‘zero’’ favorability value. The oper-ationalized ‘‘favorability’’ variable was of continuous datatype, its descriptive statistics are given in Table 5.Since the sample sizes to test the Hypothesis 1 were so

different (54 versus 283), the normality assumption for the‘‘favorability’’ variable was checked on the smaller sample,and the distribution was found to be normal (Kolmogor-ov–Smirnov p ¼ 0.200, Shapiro–Wilk p ¼ 0.467). Testresults for the Hypothesis 1 are given in Table 6 and theywere significant at the 0.1 level.

uency Score Variable Frequency Score

1.36 Alcoholism 6 �1.75

1.36 Hardworking 6 1.69

1.61 Festive 5 1.78

�0.41 Contrasts 5 1.06

�1.44 Happy 5 1.83

�1.56 Uncomfortable 5 �1.36

1.58 Serene 4 1.53

�1.19 Safe 4 1.64

�1.42 Hopeful 4 1.53

1.44 Ruthless 4 �1.53

1.56 Seedy 4 �1.28

�0.33 Historical 4 1.67

�1.19 Unpleasant 3 �1.68

1.97 Relaxing 2 1.47




4.3. Research question 3: uniqueness images

To find what unique places and features US pleasuretravelers associated with Russia, responses to question Q3were analyzed. The CATPAC procedure on the pooleddata was run, and 40 most frequent words indicating theunique Russian features were identified. Some words weregrouped together (e.g., ‘‘architecture’’ and ‘‘buildings’’) toreinforce concepts. As a result of the grouping process, thefinal set of Russia’s uniqueness variables was produced. Atable of synonyms was constructed and used as input forthe WORDER program. Occurrences of every uniquenessvariable were counted and entered into the SPSS database.Responses like ‘‘do not know’’ were included into thefrequency analyses as having ‘‘0’’ frequencies. As can beseen from Table 7, the list of unique Russian features isnearly exhaustive. The group of past visitors displayed abetter knowledge of unique Russian features.

Table 6

Favorability variable: visitors vs. non-visitors

Visitation N Mean Levene’s test for equality of

F Sig

Visitors 54 0.808 3.572 0.0

Non-visitors 283 0.235

Table 7

Uniqueness images

# Unique features All respondents 336

Frequency Mean

1 St. Petersburg 113 0.34

2 Red Square 92 0.27

3 Kremlin 75 0.22

4 Moscow 73 0.22

5 Hermitage/winter palace 44 0.13

6 Churches/cathedrals 38 0.11

7 Museums 37 0.11

8 Art 35 0.10

9 Architecture 26 0.08

10 Czars (imperial Russia) 25 0.07

11 Palaces 22 0.07

12 Cruises 15 0.04

13 Summer palace 12 0.04

14 Siberia 11 0.03

15 Small towns 9 0.03

16 St. Basil’s cathedral 8 0.02

17 Lenin’s tomb 8 0.02

18 Onion-shaped domes 8 0.02

19 Black Sea 8 0.02

20 Trans-Sib 8 0.02

21 Volga River 8 0.02

22 Leningrad 4 0.01

23 Chernobyl 3 0.01

24 Baikal 3 0.01



4.4. Research questions 4 and 5: common destination

attributes

With respect to attribute-based items, this studyclosely followed Echtner and Ritchie’s (1993) framework.Prior to analyzing the attribute-based items, eight nega-tively formulated statements were re-coded in positive forthe consistency of measurement and ease of resultsinterpretation. In Table 8 the attributes are arranged frommost to least favorably assessed, based on the whole sampleof responses. Attributes are considered positively or nega-tively assessed if their mean is below or above the neutral‘‘3.00’’ value, respectively. Hypothesis 1 test results are givenin the last column of Table 8. As can be seen from the table,the past visitor group gave a more favorable assessment ofRussia’s destinath Varimax rotation was employed to reducethe 44 destination attributes into nine factors. Ten attributes(nature preserves; nightlife/entertainment; costs/price levels;

variances t-Test for equality of means

nificant t df p-Value

60 1.726 335 0.085

Visitors n1 ¼ 54 Non-visitors n2 ¼ 283

Frequency Mean Frequency Mean

25 0.46 88 0.31

19 0.35 73 0.26

11 0.20 64 0.23

23 0.43 50 0.18

19 0.35 25 0.09

10 0.19 28 0.10

11 0.20 26 0.09

11 0.20 24 0.08

4 0.07 22 0.08

8 0.15 17 0.06

9 0.17 13 0.05

8 0.15 7 0.02

10 0.19 2 0.01

3 0.06 8 0.03

7 0.13 2 0.01

4 0.07 4 0.01

3 0.06 5 0.02

1 0.02 7 0.02

1 0.02 7 0.02

1 0.02 7 0.02

1 0.02 7 0.02

1 0.02 3 0.01

0 0.00 3 0.01

1 0.02 2 0.01



ARTICLE IN PRESS

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 0.000��

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 0.000��

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 0.000��

Transportation 3.21 0.73 3.02 0.92 3.25 0.69 0.034�

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 0.023�

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 0.041�

Crowdedness 3.60 0.70 3.83 0.75 3.55 0.68 0.007��

Economic development 3.84 0.71 3.87 0.73 3.83 0.71

�Significant at 0.05 level.��Significant at 0.01 level.

S. Stepchenkova, A.M. Morrison / Tourism Management ] (]]]]) ]]]–]]] 9

accessibility; climate; crowdedness; rest/relaxation; chanceto see how people really live; atmosphere; and arts) hadeither low communalities or factor loadings and were takenout to improve the characteristics of the solution. The finalKMO measure of sampling adequacy was 0.902; com-munalities ranged from 0.500 to 0.779; all factor loadingswere greater than 0.40. The total variance explained was61.05%. The results are given in Table 9. The factors wereself-explanatory and were named as Traditional Tourism(Factor 1); Infrastructure (Factor 2); Niche Tourism



(Factor 3); Safety (Factor 4); History (Factor 5); Food& Culture (Factor 6); Service (Factor 7); Adventure(Factor 8), and Family/adult (Factor 9). Factor 9 consistedof a single attribute; however, taking it out reduced thecharacteristics and interpretability of solution. The percen-tage of variance explained as well as the high factor loadingjustified retaining it. Cronbach’s alpha was adequate for allfactors but Factor 8. All cross loadings made sense fromthe solution interpretability point of view. For example,Scenery from Factor 1, Traditional Tourism, also loaded



ARTICLE IN PRESS

Table 9

Destination image factors

Factors F1

traditional

tourism

F2

infrastructure

F3

niche

tourism

F4

safety

F5

history

F6

food

and culture

F7

service

F8

adventure

F9

family

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 �0.426

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

S. Stepchenkova, A.M. Morrison / Tourism Management ] (]]]]) ]]]–]]]10

on Factor 3, Niche Tourism, along with such items asNatural Resources, Fishing/Hunting, Cruises, Beaches,and Trans-Sib.

5. Discussion

5.1. Implications for the FTA

Although Russia is one of the major world touristdestinations (WTO, 2006b), it has not received enoughacademic attention to date. Thus, this study partly fills thegap by assessing the country’s destination image among USpleasure travelers, one of the most affluent travel markets inthe world. The implications of the study have relevance tothe current FTA initiative to build a successful Brand Russia.



Advertising and promotion of Russia to the interna-tional traveler has been very minimal in terms of financialresources in comparison to the efforts of other majordestinations. In 2003, prior to this research, the Russianpromotional budget on the federal level was USD 3.0million (Izvestia, issue 01.21.05), which was two timesless than what was spent by Paris or Singapore alone.The result of insufficient advertising has been a lackof awareness about Russia’s tourist features as wasindicated by the current study. The share of respondentswho put ‘‘don’t know’’ as the answer to the questionQ3 about unique Russian features was 19%. The trulyunique Russian natural resources that are included inthe UNESCO World Heritage List, such as the GoldenMountains of Altai, Volcanoes of Kamchatka, Virgin Komi




Forests and others, were not mentioned at all. Lake Baikalwas mentioned by three people only. While a number ofrespondents mentioned Russia’s countryside, small townsand villages, no specific names emerged.

With regard to the other two open-ended questions,particularly about affective images, the problem was notthat American pleasure travelers knew little about Russia.The survey respondents knew various things about thecountry, but their perceptions were often unfavorable. Outof 42 affective image variables, 20 had negative favorabilityscores, and out of 337 responses, 129 and 59 had negativeand zero favorability values, respectively. The ‘‘Soviet era’’image still lingered. Poor people, country, lodgings, andfood choices were often present in the responses to Q1about the stereotypical images. ‘‘Poor’’, ‘‘undeveloped’’,‘‘hostile towards Americans’’, ‘‘ruthless’’, ‘‘depressing’’,and ‘‘unsafe’’ country emerged from about half ofresponses to Q2. Such attributes of the Soviet era, as theCold War, Lenin’s tomb, Stalin, and Leningrad, were alsomentioned.

The survey respondents did not agree whether Russianpeople were friendly or not, which was registered in theiranswers to both Q1 and Q2. Respondents who thoughtRussian people to be friendly often added such descriptorsas ‘‘somber’’ and ‘‘reserved’’. These attitudes can bepartially explained by the age of the respondents, morethan 70% of whom were more than 55 years old. Anotherpossible explanation is the complicated procedure ofobtaining a Russian visa. The lack of positive materialsabout Russia in the US general media also plays a role inAmerican pleasure travelers’ negative perceptions of thecountry. The attribute-based ‘‘hospitality-friendliness’’item indicated that visitors thought Russian people werefriendlier (mean 2.06) than non-visitors (mean 2.52).However, the ‘‘hospitality-friendliness’’ perceptions ofnon-visitors are very important for the FTA, since theymight interfere with the desire to go Russia. No countrythat wants to develop a strong tourism sector can afford tobe perceived as unfriendly to visitors. The brandingapproach might be the answer to this problem, since thevisitor’s satisfaction is in large part a matter of expectations(Chon, 1990). Careful branding of the Russian nation asthe reserved people who are cordial to guests and open andwarm to friends might be successful. To reinforce thepoliteness/cordial perception, extensive human resourcestraining programs in the hospitality and tourism sectorare also of primary importance and should be initiated bythe FTA.

With regard to functional attributes, significant differ-ences were registered for 19 items with visitors giving morefavorable assessments. This is a very interesting finding forthe FTA because it suggests that quality of Russia’s touristoffer is, in fact, better than the non-visitors think it is.Given that no significant differences were registeredbetween visitors and non-visitors in terms of demographiccharacteristics, the differences in evaluations can beattributed to the differences in the actual and perceived



Russia’s tourism attributes. The results indicated thatadequate promotional information is needed to correct thenegative perceptions of non-visitors.Several of Russia’s functional common attributes such as

economic development, accessibility, shopping facilities,cleanliness, accommodations, beaches, transportation,restaurants, and sports activities were ranked negatively(mean score higher than 3.0) by the respondents (seeTable 8). Four of these items—transportation, restaurants,shopping facilities, and sport activities—made up aseparate Infrastructure factor, and two more items—economic development and accommodations—had load-ings greater than 0.40 on this factor (see Table 9). Thisindicated that the level of infrastructure is a considerationfor US pleasure travelers in the process of destinationselection. Therefore, promotion of tourism types that areless sensitive to levels of infrastructure development isadvisable, since they potentially have a higher probabilityof success (Ilyina & Mieczkowski, 1992). These tourismtypes are also less sensitive to the service levels, with servicebeing another important consideration for potentialtravelers.As this study indicated, ‘‘traditional tourism’’ has the

strongest position image-wise in the minds of US pleasuretravelers (see Table 9). Historical sites and museums,capital and provincial cities rich in architecture andcultural heritage, beautiful scenery, and opportunities tointeract with Russian people should be combined in anattractive package. Up-to-date information on the safetyand hygiene conditions, as well as infrastructure levels,should be effectively communicated. Another possibility isthe Trans-Siberian journey with stopovers in unique naturepreserves and cultural and historical locations. The levelsof comfort, service, and infrastructure of such a trip arehigh for the first- and second-class ticket holders. Given theaverage age of the ATC members, they might not be theaudience for adventure or eco-tourism travel offers.Hypothesis 1 addresses the relationship between image

and visitation. As indicated in Section 2.1, the nature ofthis relationship is complex and multi-faceted. The act ofvisiting a destination can certainly change the image onehas of that destination. This can best be examined in termsof pre- and post-visitation images, which were not availablein this study. In turn, the favorability of a destination’simage can influence whether one chooses to visit thedestination in the first place. Therefore, association betweenimage and visitation is a two-way cause–effect relationship.However, the authors feel that, from a marketing stand-point, the direction of the relationship is not as importantas the existing ‘‘image-visitation’’ association itself. ‘‘Themore favorable the image is, the more likely visitation willoccur’’ direction stresses the need for adequate advertisingof Russia in the US travel market. The ‘‘destination imagechanges as a result of actual visitation’’ direction impliesthat with regard to this study, the actual Russian offer(assessed by the past visitors) is better than the perceivedone (assessed by non-visitors), which again highlights the




necessity of adequate marketing communications to variousgroups of potential first- and repeat visitors.

5.2. Generalizability of results

Generalizability of the results was a concern in thisstudy. Does the obtained sample of ATC members trulyrepresent American leisure travelers? To examine thisquestion, three comparisons were made: (1) between ATCmembers and US pleasure travelers to Europe; (2) betweenpopulation under study (ATC members with Internetaccess) and the whole ATC membership; and (3) betweenthe obtained sample and the population under study. First,to answer how well ATC members represent the entirepopulation of US long-haul tourists, the entire ATCmembership profile (Morrison, So, Beldona, Feng, &Stepchenkova, 2004) was qualitatively compared to theprofile of a typical US traveler to Europe (European TravelCommission (ETC), 2001). US outbound pleasure travelerstend to be more highly educated than the US adultpopulation as a whole and wait until they are older to dothe bulk of their international long-haul travel. Addition-ally, travelers to Europe are more affluent than the averageUS outbound traveler, and three-quarters of them travel ascouples. The proportion of younger members in the ATC istwice as small as that of American travelers to Europe;therefore, it was concluded that ATC members wererepresentative of the older US pleasure travelersgroup. Second, the sample of ATC members obtained inthis study was compared to the overall ATC membershipprofile. Significant differences were found for the ‘‘age’’,‘‘education’’, and ‘‘job’’ variables. Respondents of thisstudy were older and more educated, and had a largershare of professionals and retirees. This finding wassomewhat expected, since the population of this studywas limited to ATC members with Internet access. Whilethe comparison suggested that the study sample wasnot representative of the entire ATC membership, theprofile of the respondents did correspond to that ofthe older, affluent, and well-educated US pleasure travelersto Europe. Finally, the low overall response rate (�7%)did not allow conclusion that the opinions of peoplewho participated in the survey were representative of theentire population under study (ATC members withInternet access). To check for non-response bias, twogroups of the survey respondents, 1st and 2nd stage, werecompared. The groups were found to be the same for the‘‘visitation’’ and all the demographic variables but income,a result that does not disconfirm that the obtained sampleand the population under study are the same. Therefore,while the question of how representative the sample was ofthe entire ATC membership with Internet access stillremains, studying the sample group is very valuable from amarketing standpoint because of their demographiccharacteristics which indicate economic power and predis-position for long-haul travel.



5.3. Limitations and further research

The study confirmed that the parsimonious set of 35scale items on common destination attributes proposed byEchtner and Ritchie (1993) can be successfully used for avery broad range of destinations, including such large anddiverse countries as Russia. Factor analysis conducted on a35-item set resulted in seven factors, the interpretation ofwhich had much in common with the factors obtained byEchtner and Ritchie (1993). Adding Russia-specific attri-butes made the factor solution less stable, and 10 attributeshad to be taken out. The resulting factors were essentiallythe same with one notable exception: Russia-relatedattributes mostly fell into the Niche Tourism factor. Thissuggests that including new, destination-specific attributes,into a set of well established attributes should undergo arigorous selection procedure, similar to that which wasemployed by Echtner and Ritchie (1993).Russia as a tourist destination does not equal Russia as a

country. Kotler and Gertner (2002, p. 251) pointed out that‘‘a country’s image results from its geography, history,proclamations, art and music, famous citizens and otherfeatures’’. Destination and country images are overlappingconstructs (Mossberg & Kleppe, 2005), and Russia’sdestination image is undoubtedly influenced by thecountry’s image, however, it is not clear to what degree.Therefore, it is important to assess how Russia’s destina-tion image is affected by the often negative coverage ofRussia as a political entity in the US general media. Thequestion as to whether these two images can be separatedin the minds of potential travelers to Russia has directrelevance to successful building of Brand Russia.This study dealt with the image of Russia as a travel

destination among US pleasure travelers. However, the USis only one potential market for Russia’s inbound tourism.The large distance between the two countries might have anegative effect on how Russia is perceived by US travelersas suggested by Reilly (1990). Other, geographically closermarkets might be better suited for focused promotionalefforts of the FTA, because they might already possess amore favorable and accurate image of Russia that wouldrequire less effort and finance to enhance and positivelyinduce.

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