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Вестник Нижегородского университета им. Н.И. Лобачевского. Серия: Социальные науки, 2015, № 2 (38), с. 85-96
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УДК 316
ФАКТОРЫ, ВЛИЯЮЩИЕ НА ПОВЕДЕНИЕ РОССИЙСКИХ ТУРИСТОВ ПОСЛЕ ПОСЕЩЕНИЯ НИЖНЕГО НОВГОРОДА
© 2015 г. Г. Симановская, С. Степченкова
Университет Флориды, США svetlana.step@hhp.ufl.edu
Поступила в редакцию 05.05.2015
Нижний Новгород является одним из одиннадцати городов России, в которых в 2018 г. пройдёт Чемпионат мира по футболу. Ожидается, что мероприятие увеличит число прибывающих в город внутренних и иностранных туристов и привлечёт внимание к вопросам совершенствования туристического предложения и к формированию положительных впечатлений от посещения города у туристов. В статье исследуются факторы эффективности дестинации, восприятия рисков, осведомлённости и профиля туристов, поскольку именно эти факторы влияют на отношение туристов к дестинации после ее посещения в рамках внутренних поездок. Данные были получены в 2013 г. через онлайн-опрос лиц, посетивших г. Нижний Новгород. Было установлено, что на намерение вновь посетить дестинацию и готовность рекомендовать город в социальных сетях, а также при личном общении влияют эффективность дестинации и проблемы, связанные с проездом. Результаты исследования могут помочь в формировании стратегии развития туризма в Нижнем Новгороде, определении областей для распределения ресурсов и позиционирования Нижнего Новгорода среди других исторических российских городов в Европейской части страны.
Ключевые слова: эффективность дестинации, отечественные туристы, Нижний Новгород, онлайн-опрос, отношение после посещения, восприятие риска, городская дестинация.
Being a vast country geographically, the Russian Federation has many tourist resources - historic, cultural, natural, ethnographic, etc. - at its disposal, but its potential as a premier tourism destination has not yet materialized (Horner & Swarbrooke, 2004). To realize that potential, attention should be given not only to traditional tourist centers such as Moscow and St. Petersburg, but to other regions as well. Cities have always been and continue to be popular tourist destinations, although different cities are visited for different reasons (Borg, 1994; Peters & Pikkemaat, 2003). "Big cities" and "interesting old cities" are part of the Russian destination image (Stepchenkova & Morrison, 2008), and Nizhny Novgorod (Nizhny) is considered one of these cities. Nizhny is among the five largest cities in Russia with a population of 1.3 million people, and it is often called the third capital of Russia, after Moscow and St. Petersburg. The city was founded in 1221 on two great rivers, the Volga and the Oka, and is famous for its historic places, cultural significance, outstanding architecture, and picturesque views. There are 874 objects of cultural and historic interest in the city of Nizh-ny Novgorod (Kuftiryov, 2011), with the Kremlin fortress epitomizing the city's historic, architectural, and cultural heritage. The Nizhny Novgorod Region possesses several hundred museums, galleries, and exhibition centers, as well as important
national and world heritage sites Makariev Monastery and Serafimo-Diveevsky Monastery (Avralev & Efimova, 2011).
Russia will host two mega-events which are expected to bring an influx of both international and domestic tourists to various parts of the country: the 2014 Winter Olympic Games in Sochi and the 2018 FIFA World Cup, where Nizhny Novgorod will be one of eleven cities to host the event. Besides building new tourist infrastructure, hosting mega-events sharply increases destination visibility and awareness, enhances destination image, and translates tourists' evaluation of destinations performance into word-of-mouth post-visitation behavior (Gartner, 1989; Gibson et al., 2008; Kaplanidou, 2009; Ritchie & Smith, 1991). Prior to the mega-events of such scope and influence, studies of destination tourism from various perspectives are advisable. Tourism research potentially can help the Ministry of the Development of Small Business, Consumer Market and Services in Nizh-ny Novgorod Region, a government body responsible for development of tourism industry in the area, coordinate the tourism-development strategies in the city and better prepare to meet tourist needs in the future.
In the competitive marketplace, with many destinations for tourists to choose from, the destination management organizations pay attention to tourists'
evaluations of destination performance, risks associated with visiting the destination, and postvisitation behavior including word-of-mouth and intention to revisit. Destinations, as complex products, evaluated by current and potential tourists along a number of attributes (e.g., climate, hotels, attractions), compared to and contrasted against available alternatives, and results of this mental process form a basis of destination choice (Gensch, 1978). Making a final decision about the destination, travelers also consider risks associated with the trip (e.g., Sonmez, 1998; Sonmez & Graefe, 1998b; Floyd et al., 2004). Perceptions of high risks may result in a decrease in visitations to the destination, both for international and domestic tourists (Sonmez & Graefe, 1998a). In addition, tourists communicate destination image and their experiences with the destination to their friends, relatives, co-workers, and other people, both offline and online. This word-of-mouth has been recognized as a powerful factor in influencing destination perceptions and intention to visit (e.g., Opper-man, 2000; Kozak, 2001; Simpson & Singuaw, 2008). In the "tourist-destination" relationship, characteristics of the tourists are very important. Familiarity with the destination (e.g., first-timers or repeat visitors), primary reason for visiting (e.g., leisure or business), overall risk profile, travel characteristics and party composition, demographic and psychographic information are all been shown to influence tourist behavior (e.g., Lehto et al., 2001; Sonmez & Graefe, 1998; Um et al., 2006).
Thus, given the need for studying tourists to Nizhni Novgorod, Russia, this study aims to answer the following research questions:
1. How do tourists to Nizhni evaluate destination performance?
2. How do tourists perceive risks associated with travel to Nizhni?
3. Which factors - destination performance, risk perceptions, familiarity, or tourist type - are the best predictors of intention to revisit Nizhni?
4. Which factors - destination performance, risk perceptions, familiarity, or tourist type - are the best predictor of positive word-of-mouth activity about Nizhni?
LITERATURE REVIEW
Destination Performance
The importance of destination performance construct has been recognized in academic literature (e.g., Kozak, 2002; Um et al., 2006), as the feedback from visitors show strengths and weaknesses of the destination and can be used to compare destinations to one another (Kozak, 2002). Performance evaluations bring attention to poorly performing attributes, so that these areas can be
brought up to standard (Kozak, 2002). On the tourist part, the level of product and/or service performance can cause satisfaction or dissatisfaction with the experience at the destination (Kozak, 2002; Churchill & Surprenant, 1982; Tse & Wilton, 1988; Um et al., 2006). Two major schools in measuring customer satisfaction relevant to the tourism industry are identified in the literature (Kozak & Rim-mington, 2000). One school measures the gap between expectations prior to the trip and the actual performance of the destination (Chon & Uysal, 2005; Churchill & Surprenant, 1982; Parasurman et al., 1985; Pizam & Milman, 1993). The other school, known as Nordic school, focuses on the destination performance only, stating that satisfaction is the result of the actual performance of the destination, thus, disregarding the expectations a person had before traveling (Pizam et al., 1993). The Nordic model shows that the destination performance evaluations and the initial expectations the person has about the destination prior to the visit should be considered independently (Tse & Wilton, 1988; Yoon & Uysal, 2005). The model that disregards expectations is often preferred because it can be used even in situations when visitors know little about the destination prior to visiting it (Yoon & Uysal, 2005).
Product performance can be characterized as post-consumption evaluative judgments (Mano & Oliver, 1993). While destinations are much more complex products than fast-moving consumer goods and are characterized by the high level of consumer involvement at all stages of product consumption, their performance is often measured as the sum of tourists' evaluations of various destination attributes (Danaher & Arweiler, 1996; Churchill & Surprenant, 1982; Qu & Li, 1997; Kozak & Rimmington, 2000). Some of these attributes like for example, climate, accommodations, or restaurants, are of a more tangible nature, while other attributes, like, for example, level of development, safety, or service, are of a more psychological nature (Echtner & Ritchie, 1993). Some attributes are common to all destinations (e.g., accommodations), while other are destination-specific (e.g., beaches). For the city of Nizhni Novgorod being an urban destination, the literature review was conducted with respect to the most parsimonious instrument to measure urban destination performance. The survey by Haywood & Muller (1988) was adopted for the study.
Risk Perception
Risks associated with travel to a particular destination influence the lasting destination image formation (Sonmez & Graefe, 1998b). These risks can even outweigh the favorably perceived features
that the destination possesses and alter the decision-making process (Floyd et al., 2004; Sonmez & Graefe, 1999a, 1998b). Tourism products are intangible for the most part and are consumed at the time of production; the consequence of this process is that the perceived risks are most likely to be high (Roehl & Fesenmaier, 1992). The higher the perceived risks, the more tourists will tend to avoid the destination, resulting in a decrease in visitations (Floyd & Pennington-Gray, 2004; Fuchs & Reichel, 2006). High perceived risks can influence tourists to pursue other travel plans, change their destination choice, modify their travel behavior, or search for additional information if they decide to continue with their travel plans (Reisinger & Ma-vondo, 2005).
The need for safety, security, and stress-free trips is one of the key determinants of future travel intentions (Reisinger & Mavondo, 2005). As a result, one of the factors that influence the process of decision-making is often associated with a choice, the consequences of which are uncertain, and some of these consequences are more desirable than others (Fuchs & Reichel, 2006; Roehl & Fesenmaier, 1992; Sonmez & Graefe, 1998b). Risk in tourism is defined as perceptions and experiences of tourists during the process of purchasing and consuming travel services (Tsaur et al., 1997). The degree of risk associated with traveling depends on several factors such as, for example, means of transportation used, the facilities and activities offered at the destination, and the customs and environment in the area, to name just a few (Tsaur et al., 1997). Perception of risks can vary according to the tourists' characteristics as well (Barker et al., 2003; Floyd et al., 2004; Reisinger & Mavondo, 2005; Roehl & Fesemaier, 1992; Simpson & Siguaw, 2008a; Sonmez & Graefe, 1998b). Another factor contributing to the differences in the level of risk perception among travelers is previous experience with the destination, which is believes to positively influence risk perception, as tourists tend to feel safer about traveling to a destination they have previously visited (Floyd et al., 2004; Lepp & Gibson, 2003).
There are several types of risks identified by the literature, and the importance of each depends on the situation (Maser & Weiermair, 1998; Roehl & Fesemaier, 1992). The risk types related to the tourism industry were identified as (1) time - not performing on time or wasting time; (2) financial - the risk of losing money invested in a product or service if the product or service fails to meet expectations; (3) physical - the risk of physical harm, such as injury or illness; (4) psychological - the fear that the purchased product will not be compatible with
the self-image of the traveler or reflect negatively on him/her; (5) satisfaction - not living up to the traveler's expectations; (6) social - the risk that the purchase will not conform to the visitor's standards, lead to losing personal and social status, and/or lowering status; and (7) functional or performance - not performing or delivering the benefits to the tourists, and not meeting their needs (Floyd et al., 2004; Fuchs & Reichel, 2006; Roehl & Fesemaier, 1992). Three other types of risks, i.e., health, political instability, and terrorism, were added later, of which terrorism and political instability were found to be of particular concern (Lepp & Gibson, 2003; Sonmez & Graefe, 1998a; 1998b). The importance of specific types of risks depends on individual differences among travelers (Roehl & Fesenmaier, 1992; Sonmez & Graefe, 1998b).
Post-Visitation Behavior
The revisit intention, as well as positive word-of-mouth, are considered to be the most important behavioral consequences in destination experience (Chen & Tsai, 2007; Opperman, 2000; Simpson & Singuaw, 2008; Wang & Hsu, 2010). The intention to revisit has been studied in the tourism literature and is considered to be the sign of the destination loyalty (Assaker et al., 2011; Chi & Qu, 2008). Five main reasons why people revisit destinations were identified: (1) risk reduction associated with the content of the particular destination, including the unawareness of the alternatives or the fear that these alternatives are not as desirable as known destination; (2) risk reduction associated with finding the same kind of people; (3) emotional attachment to a destination; (4) further exploration of the destination; (5) showing the destination to other people and sharing the experience (Gitelson & Crompton, 1984). Based on the tourists' temporal destination revisit intention, the following tourists segmentation was proposed: (1) continuous repeaters - those who visit the destination with consistently high revisit intentions over time; (2) deferred repeaters - those tourists who have low level of revisit intentions in the short-term, but high revisit intentions in the mid-term and long-term; and (3) continuous switchers - travelers with consistently low revisit intentions over time (Feng & Jang, 2004). The timeframes can be considered as following: short-term - less than one year, mid-term - 1-3years, long-term - 3-5 years (Feng & Jang, 2004). Satisfaction with the trip and tourists' positive experience at the destination were found to be an important antecedent of repeat visitations (Bigne et al., 2001; Fakeye & Crompton, 1991; Hui et al., 2007; Kozak, 2001; Murphy et al., 2000; Pritchard & Havitz, 2006).
Word-of-mouth can be defined as "informal, person-to-person communication between a perceived noncommercial communicator and a receiv-
er regarding a brand, a product, an organization or a service" (Harrison-Walker, 2001, p. 63). Word-of-mouth is an indicator of the tourist's desire to continue the relationship with the destination as well as one of the most reliable sources of information that people take in considerations in their decision-making processs (Chi & Qu, 2008; Choi et al., 2011; Litvin et al., 2008; Opperman, 2000; Simpson & Singuaw, 2008; Wang & Hsu, 2010). The negative word-of-mouth has been shown to have a devastating impact on the destination selection process (Litvin et al., 2008; Morgan et al., 2003). Those who have visited the destination several times or have been to the destination recently tend to provide more positive word-of-mouth, simply because they can easily recall the experience (Oppermann, 2000). Word-of-mouth can be considered as the least expensive advertisement tools, as well as one of the most powerful, in affecting people's feelings and behavior, in particular, friends and family of those who visited the destination (Simpson & Singuaw, 2008; Tiefenbacher et al., 2000).
Familiarity and Tourist Types Factors
The literature review indicates that evaluations of destination performance and risks associated with travel to the destination influence each of the two types of post-visitation behavior: intention to revisit and positive word-of-mouth. Scholars also emphasize familiarity with the destination as an important factor influencing destination perceptions and the desire of tourists to revisit it (Baloglu, 2001; Milman & Pizam, 1995; Stepchenkova & Morrison, 2008). Familiarity represents a key marketing variable in segmenting and targeting the potential visitors. Familiarity can be understood as previous experience with a destination (experience dimension) and knowledge about it (information dimension). Familiarity as experience can be measured as the number of previous visits to the destination or as "first-timers" vs. "repeaters" distinction. The information dimension of familiarity has been previously operationalized as having friends or relatives at the destination (Stepchenkova & Morrison, 2008) or following news about the destination. Those tourists who are familiar with the destination are, generally, more favorable towards that destination and more likely to travel there (Baloglu, 2001; Milman & Pizam, 1995; Wang & Hsu, 2010). Primary purpose to visit destination, which has been conceptualized as tourist type, that is, leisure, business, VFR, or other, is another market segmentation variable, helpful for destination marketing organizations in their product development and communication efforts.
The study investigates factors of destination performance, risk perception, familiarity, and tour-
ist type as they affect post-visitation behavior in the context of domestic travel to a large urban destination.
METHODS
Instrument
The instrument consisted of the following groups of questions: (1) respondents' profile, (2) evaluation of destination performance, (3) perception of travel risks, and (4) post-visitation behavior. The first group of questions asked about the purpose of the trip, the frequency of visitation in last 4 years, the length of stay during the latest trip, the primary purpose for visiting Nizhni Novgorod, as well as demographic information. The second group of questions asked about destination performance along 17 dimensions which were taken from the urban experience survey by Haywood & Muller (1988) with minor adaptation to the case of Nizhny. All destination performance items were measured on the 5-point Likert scale (1 = strongly agree; 5 = strongly disagree). The third group of questions dealt with perceptions of risks associated with travel to Nizhni. The items were taken from the literature (Floyd et al., 2004; Floyd & Pennington-Gray, 2004) with minor adaptations and used the 5-point Likert scale (1 = strongly agree; 5 = strongly disagree). The last group of questions included items that measured post-visitation behavior as intention to revisit the destination and as engaging into a positive word-of-mouth (PWOM) behavior after visitation. The intention to revisit measure consisted of three items (short-term, long-term, and overall intention to revisit) adopted from Lee et al. (2004) and used the 5-point Likert scale (1 = strongly agree; 5 = strongly disagree). Five PWOM "yes"/"no" items reflected whether a particular tourist engaged in speaking positively about Nizhni to their friends, family, and other people, as well as online (Jang & Feng, 2007; Lee et al., 2004). The number of "yes" answers represented the person's composite PWOM score.
Data Collection
The target population of the study was defined as Russian domestic tourists who have been to Nizhny Novgorod in the last 4 years (2009-2012). Domestic tourists were understood as people who travel away from home for a distance at least 50 miles (one way) for business, pleasure, personal affairs or any other purpose except to commute to work, whether s/he stays overnight or returns the same day. The time frame of four years was set to avoid difficulties in recalling tourist experiences with the destination (Kozak, 2002; Kozak & Rim-mington, 1999). The data were collected in the last two weeks of January, 2013 through social networks Vkontakte and Facebook. Several "open"
Table 1: Respondents' Profile
Variable Levels Freq Valid % Variable Levels Freq Valid %
Gender Male 89 32.6 Familiarity First-comers 70 25.0
Female 181 66.3 Repeat visitors 210 75.0
Prefer not to answer 3 1.1
Education Less than High School 3 1.1 Length of stay One-day trip 57 20.5
High School Graduate 12 4.5 during the most Overnight 221 79.5
Some College 57 21.3 recent visit
College Degree 166 62.3
Technical School 14 5.2
Advance Degree 9 3.4
Prefer not to answer 6 2.2
Age 18-24 128 48.5 Primary reason Leisure 90 32.3
25-34 93 35.2 for visiting Business 67 24
35-44 16 6 Nizhni VFR 104 37.3
45-54 4 1.5 Other 18 6.4
65 and older 2 0.8
Prefer not to answer 21 8
Marital Single 155 57.6 Number of visits 1-2 99 35.4
Status Partnered/Married 93 34.6 in the kast 4 3-5 52 18.6
Divorced 15 5.6 years 6-10 70 25
Separated 2 0.7 11 and more 59 21
Prefer not to answer 4 1.5
Income Very good 17 6.4
Good 85 32
Average 136 51.1
Bad 11 4.1
Very bad 1 0.4
Prefer not to answer 16 6
and "closed" groups and communities within these social networks were identified as suitable for the study, based on their primary purpose (i.e., travel, Nizhni Novgorod) and the number of participants. Moderators of the communities were approached with the request to help with the study and post the invitation to participate in the study on the group forums and community message boards. Two reminders were issued during the two weeks of data collection. The total number of qualified responses was 468. Responses that were less than 50% complete and responses that were filled out by those who stayed in Nizhny Novgorod for more than 6 months were removed. The number of usable responses was 283.
Data Analysis: Regression Model
To find out the best predictor of post-visitation behavior, the regression analysis was conducted. The first dependent variable was intention to revisit (REVISIT), and the second dependent variable was composite PWOM (positive word-of-mouth) score. Based on the literature review, several predictors of post-visitation behavior were identified, such as reasons for visiting, how well tourists know the destination, how risky they perceive the destination
to be for travel, and how they perceive that destination's tourism offer. Reasons for visiting the destination were operationalized by the variable tourist type (TT) that reflected whether a person was leisure, business, or VFR (visiting friends and relatives) tourist. The familiarity variable was opera-tionalized as the number of previous visits to Nizh-ny Novgorod (FAMILIAR). The overall risk perception (RISK) and the overall destination performance (PERFORM) variables were the averages of the respective survey items. Thus, the models were expressed as follows:
Model 1: REVISIT = a + b TT + b2 FAMILIAR + bs RISK + b4 PERFORM + e
Model 2: PWOM = a + bj TT + b2 FAMILIAR + bs RISK + b4 PERFORM + e RESULTS Respondents' Profile
Questions about respondents' gender, marital status, age, education, and income were analyzed to obtain the respondents' demographic profile (Table 1). In the sample, two thirds were female (66.3%) and approximately one third was male (32.6%). A split between single and married or partnered was 57.6% and 34.6%, respectfully. Age was reported
Table 2. Destination Performance
Variable N Mean St. Dev. Skew Kurt
Pleasurability of walking 280 4.43 0.97 -0.78 0.84
Scenic beauty 279 4.30 1.06 -1.75 2.62
Parks and greenery 279 3.81 1.30 -1.30 1.26
Choice of restaurants 278 3.69 1.44 0.08 -1.49
Crowding and congestion 279 3.66 1.39 -0.79 -0.20
Cultural amenities 279 3.66 1.32 -0.66 -0.72
Accessibility 280 3.60 1.31 -0.86 -0.02
Climate/weather 278 3.51 1.03 -0.74 -0.64
Cleanliness 279 3.49 1.32 -1.09 0.66
Friendliness of locals 280 3.49 1.29 -2.08 4.32
Nightlife and entertainment 280 3.38 1.55 -1.04 0.29
Pleasurability of shopping 280 3.33 1.53 -1.15 0.57
Price levels 280 3.29 1.29 -1.03 0.08
Friendliness of personnel 279 3.07 1.68 -0.84 -0.20
Safety from crime 277 3.03 1.66 -0.82 0.40
Hotel standards 279 2.03 1.78 -0.84 0.16
Availability of healthcare 280 1.91 1.79 0.17 -1.47
PERFORM 267 3.39 0.78 -0.61 0.31
as the number of full years (M=25.85; std.dev=8.010). For convenience of reporting, age was converted to an ordinal variable of 5 levels. Most frequently reported age groups were between 18 and 24 (48.5%) and between 25 and 34 (35.2%). With respect to education, most respondents had a college degree (62.3%). As far as the financial situation is concerned, 51.1% of the respondents reported their financial situation as "neither good nor bad", while 38.4% reported it as "good," or "very good." Only 4.5% defined their financial situation as "bad" and "very bad." Overall, domestic visitors to Nizhni can be characterized as the younger, single, well educated, and financially well-off crowd.
The shares of leisure tourists (sightseeing, special event, entertainment, outdoor recreation, sporting event, and shopping), business tourists (business and education), and visiting friends and relatives (VFR) were 32.3%, 24.0%, and 37.3%, respectively. The split between first-timers and repeat visitors was 25.0% vs. 75.0%, respectively. The mean and standard deviation of the number of visits in the last four years were M=7.57 and std.dev=10.682. With respect to the most recent visit, 79.5% stayed overnight, while 20.5% came on a one-day trip. Most of the repeat visitors were VFR (43.2 %), while most of the first-timers were leisure travelers (44.3 %).
Destination Performance
Perceptions of destination performance were measured by 17 items on a 5-point Likert scale.
Descriptive statistics for each item are given in Table 2; items are ranked from the most to the least favorably evaluated. Attributes with the highest scores were Pleasurability of walking in tourist areas, Scenic beauty, and Parks and greenery. The lowest evaluation was given to such attributes as Hotel standards and Availability of healthcare. Internal reliability of the performance scale was calculated using Cronbach's alpha, which was 0.86. Item-to-total correlations indicated that no item could be removed without decreasing the overall internal consistency of the scale. The overall performance (PERFORM) variable was created by averaging means of all individual items (Table 2).
Risk Perception
Descriptive statistics were calculated to find out how tourists perceived risks associated with traveling to Nizhny (Table 3). Prior to their most recent trip, respondents thought of such risks as crime and terrorism as the most likely to occur. Disapproval of others and health risks were perceived as the least likely to occur. The survey also included an open-ended question "What is, in your opinion, the most risky thing about traveling to Nizhny Novgorod?" Among those who answered the question (30.6% of all respondents), the most common answers were crime (7.0 percent), bad traffic (3.9 percent) and bad weather (3.9 percent). Overall, for domestic tourists, risks associated with a trip to Nizhni were quite low, with a possible exception of crime. The overall risk perception (RISK) variable
Table 3: Risk Perception
Variable N Mean St. Dev. Skew Kurt
Crime 277 2.33 1.08 0.40 -0.64
Terrorism 277 1.70 0.93 1.14 0.62
Waste of money 277 1.66 0.89 1.49 2.34
Disappointing trip 275 1.62 0.94 1.62 2.21
Crisis of surrounding infrastructure 277 1.54 0.89 1.75 2.61
Natural disaster 275 1.47 0.82 1.74 2.59
Health risks 276 1.42 0.81 2.03 3.96
Disapproval of others 276 1.31 0.67 2.85 9.97
RISK 271 1.45 0.55 1.75 5.30
Table 4: Regression Model Variables: Descriptive Statistics
Variable N Mean St. Dev. Skew Kurt
REVISIT 254 4.11 1.14 -1.38 1.07
PWOM 257 3.45 1.25 -0.64 0.05
PERFORM 263 3.38 0.78 -0.61 0.32
RISK 271 1.45 0.55 1.75 5.29
FAMILIAR 274 6.89 7.26 2.23 7.18
TOURIST TYPE N LEI BUS VFR OTHER
279 89 66 102 18
was created by averaging means of all individual items (Table 3).
Post-Visitation Behavior: Regression Model
The dependent variables intention to revisit (REVISIT) and positive word-of-mouth (PWOM) were calculated as the average of the respective survey items. The initial runs of Model 1 and Model 2 indicated that the data contained outliers, i.e., cases whose standardized residuals were greater than 3.3. Four cases were removed from the data. The model was also examined to assure that the residuals were dispersed randomly. For Model 1, the plot of residuals against predicted values did not display a "funnel" shape, which is characteristic for non-constant variance. It was concluded that the homoskedasticity assumption was met for Model 1. For Model 2, moderate violations of homoscedas-ticity were detected, which may have had an impact on the regression estimates (Fox, 2005). Lastly, the data was examined for multicollinearity: the variance-inflation factor was around 1.0, which indicated the absence of multicollinearity. The descriptive statistics for all variables in regression analyses are given in Table 4.
For Model 1, three independent variables were found to be significant predictors of intention to revisit, namely, overall performance, overall risk perception, and number of previous visits to the destination. For the overall performance variable, the association is positive: the larger the overall performance score, the higher the intention to revis-
it. For the overall risk perception, the association is negative: the higher overall risk perception, the lower the intention to revisit. For the number of previous visits variable (FAMILIAR), the association is also positive: the larger the score, the higher the revisit intention. The dichotomous variable representing the primary reason to visit Nizhny (VFR versus all other categories combined) was not significant. Overall, the four variables explained about 24% of all variance in the dependent intention to revisit variable (R-square = 0.237) (Table 5).
For Model 2, two independent variables were found to be significant predictors for word of mouth, namely, overall performance and overall risk perception. For the overall performance variable, the association is positive, while for the overall risk perception, the association is negative. The tourist type variable (LEI versus other groups combined) was marginally significant. The number of previous visits was not significant in the model. Overall, the four variables explained only 17% of the variance in the dependent variable (R-square = 0.172) (Table 6).
DISCUSSION
The study looked at such constructs as destination performance, risk perceptions, and postvisitation behavior and investigated relationship between these constructs in the context of domestic tourism. Analysis on 17 performance attributes for Nizhny Novgorod, Russia showed that most attributes were assessed quite favorably, with the mean
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Table 5: Intention to Revisit Factors: Performance Evaluation, Risk Perception, Tourist Type, and Familiarity with Destination
DF SS MS F P-value
Regression 4 71.555 17.889 17.519 0.000
Residual 226 230.771 1.021
Total 230 302.326
B SE B Std. B t P-value
Constant 3.311 0.402 8.235 0.000
TOURIST TYPE (VFR) 0.226 0.139 0.950 1.633 0.104
FAMILIAR 0.024 0.009 0.153 2.562 0.011
RISK -0.634 0.126 -0.310 -5.042 0.000
PERFORM 0.436 0.090 0.290 4.832 0.000
R Sq/Adj R Sq = 0.237/0.223
Table 6: Positive Word-of-Mouth Factors: Performance Evaluation, Risk Perception, Tourist Type, and Familiarity with Destination
DF SS MS F P-value
Regression 4 61.098 15.274 11.976 0.000
Residual 230 293.345 1.275
Total 234 354.443
B SE B Std. B t P-value
Constant 2.031 0.445 4.561 0.000
TOURIST TYPE (LEI) 0.292 0.159 0.111 1.837 0.068
FAMILIAR 0.014 0.010 0.087 1.416 0.158
RISK -0.369 0.140 -0.167 -2.634 0.009
PERFORM 0.520 0.101 0.318 5.139 0.000
R Sq/Adj R Sq = 0.172/0.158
higher than 3.0. Survey respondents evaluated pleasure of walking in the tourist areas, scenic beauty, and parks and greenery the highest; while hotel standards and availability of healthcare in case of emergency were evaluated the lowest. The study showed that Nizhny Novgorod generally performs well on the environmental type of attributes such as scenery, parks and greenery which were named to be one of the predictors of the quality of the trip (Murphy et al., 2000). However, low score received on the hotel standards attribute might be a serious concern, as previous research showed that accommodation is one of the most important destination attributes as evaluated by tourists (Pritchard & Havitz, 2006). While hotel standards may not be an important attribute for VFR tourists, for leisure and business travelers this is definitely a factor affecting destination choice. This study found that people who evaluated performance of Nizhny Nov-
gorod higher reported higher intentions to revisit the destination.
Survey respondents were asked to report perceptions of risks associated with their travel to Nizhny Novgorod that they held prior to their most recent trip to the city. In general, risk perceptions were low on all individual items, but respondents evaluated risk of being a victim of a crime as the highest. Open-ended responses also mentioned the risk of being a crime victim most often. One of the reasons for low risk perceptions might be the fact that study was conducted among Russian domestic travelers who does not perceive the risk of travelling to Nizhni Novgorod as being higher than in the place where they currently reside. The fact that respondents did not express high levels of risk perceptions associated with travel to Nizhni Novgorod is a good sign for the destination DMO (Fuchs & Reichel, 2006). The evaluation of crime as the risk
that is most likely to happen reflects the awareness of domestic tourists of a relatively high level of crime in Nizhni Novgorod. Data show that there were 1,974.2 crimes committed per 100,000 people in Nizhny Novgorod region in 2011, while the average number of crimes in Russia was lower in the same year constituting 1,694.5 per 100,000 people (Smirnova, 2012). It is a serious concern, as the previous research shows that no matter whether a tourist or a local resident is a target of crime, if crimes occur with a relatively high frequency, it will affect the destination image and result in decline in the number of visitations to the destination (Pizam, 1999).
Destination performance, reasons for a trip, risk perceptions, as well as previous experience with the destination, affect future visits and positive word-of-mouth behavior (Haywood & Muller, 1988; Milman & Pizam, 1995; Sonmez & Graefe, 1998b; Um et al., 2006). Based on the data obtained in the study, Nizhni Novgorod has already had a base of loyal visitors, those who come to Nizhni again and again. To expand this base from primarily VFR tourist to leisure tourists and, ultimately, to business and corporate visitors is of high importance for the destination because (1) loyal customers are believed to spend more at a destination; (2) they are less sensitive to price changes; (3) they are a powerful source of PWOM, which is critical, since people tend to be influenced by negative assessments more than by positive ones (Weinberger et al., 1981); (4) they represent a stable source of revenue; and (5) they are more forgiving in case of error (Croes et al., 2010). The study also found that people who evaluated performance of Nizhny Novgorod higher, reported the higher levels of engagement in PWOM activity as well. This is in line with previous research which showed that destination performance contributes to the overall satisfaction with the trip, and overall satisfaction, in turn, is a predictor of post-visitation behavior (Chi & Qu, 2008; Haywood & Muller, 1988).
Overall risk perceptions were found to affect the revisit intention and positive word-of-mouth activity negatively: the higher the risk perception of travel to the destination was, the less likely respondents were to revisit the destination and to engage in PWOM. Familiarity with the destination, however, was found to affect intention to revisit positively: the more times respondents visited the destination in the last 4 years, the higher they evaluated their likelihood of return. Interestingly, the relationship between familiarity and PWOM was not significant in the model. While previous research showed that repeaters tend to engage in PWOM more than those who came to the destination for the first time (Op-
permann, 2000; Um et al., 2006), the relationship between the previous visitations and PWOM variables has not been extensively tested yet. In addition, the factor of being a leisure tourist was marginally significant (p-value of 0.068) in affecting PWOM. The practice of posting reviews in the context of domestic travel is not yet widely accepted in Russia. Moreover, operationalization of the PWOM variable adopted in this study as actual behavior, not as the likelihood of behavior, may have also played a role. This is one area of future research, which potentially could bring new insights into the relationships between theoretical constructs of familiarity and PWOM.
Finally, the results of regression analysis indicate that destination performance and perception of risks are the strongest predictors of post-visitation behavior, compared to reasons for travel to Nizhny Novgorod (tourist type) and familiarity with the destination. It should be pointed out, however, that both Model 1 and Model 2 explained just a portion of all variance in the behavior variable, specifically 24% and 17%, respectively. This is an expected result, since numerous other factors such as financial factor, time, initial motivation for the trip, as well as other demographic, external and internal factors, influence travelers' destination choice (Yoon & Uysal, 2005).
A non-random, self-selected sample was a limitation of the study. While respondent profile in a number of characteristics (younger, educated, and financially well-off people) matched the general profile of Russian users of social networks, the gender composition of the sample was heavily tilted towards women. Studies found that women were more likely to disclose personal information to people whom they do not know, while men were more likely to share such information with those close to them (Dindia & Allen, 1992). This difference in attitudes may explain, at least partially, the gender discrepancy in the obtained sample. Self-selection may have also influenced the survey results because those interested in the topic were more likely to respond. Those who did not participated may have different perceptions of Nizhni Novgorod as a destination, as well as demographic and psychographic profile. Future studies may include a more representative sample by conducting data collection in Russia, for example, intercepting people on the streets of the city or by means of a mailed survey. Additionally, there was an issue of translation. The survey items were initially formulated in English (adopted from other studies, adapted with minor changes, or written by the researchers), while the actual survey was conducted in Russian. While care was taken to translate, items
could have been influenced by translation. Finally, with respect to risks perception, respondents gave their answers about how they felt about their last trip to Nizhny Novgorod after their trip had actually happened. Time that passed from their last trip may have skewed their responses. It might be valuable to conduct a study measuring perceptions and expectations before the visit and post-visitation risk perception and performance evaluation of the destination, and then measure the perception gap.
In conclusion, as far as the authors know, the study conducted the first research about the city of Nizhny Novgorod, Russia, using respondents from popular Russian social network sites. The data were collected and analyzed on how visitors evaluated the destination on their most recent trip, how they perceived risks associated with travel to the destination, and in what type of post-visitation behavior they engaged after their trip. The study tested several theoretically postulated relationships between destination performance, risk perception, and postvisitation behavior in the context of domestic travel. This is a theoretical contribution of the study, since previously these relationships were tested primarily in the international context. From a practical angle, it is hoped that the results of the study will aid in strategizing tourism development in Nizhny Novgorod, identifying areas for resource allocation, and positioning Nizhny Novgorod among other historic Russian cities in the European part of the country. They may help improve the city's tourist offer and make the destination more desirable for domestic tourists in preparation for the mega sport events that the city is to host in the near future.
References
Assaker G., Vinzi V.E. & O'Connor P. (2011). Examining the effect of novelty seeking, satisfaction, and destination image on tourists' return pattern: a two-factor, non-linear latent growth model. Tourism Management, 32, 890-901.
Avralev N.V. & Efimova I.V. (2011). Local authorities activity analysis in the Nizhny Novgorod region in the sphere of tourism. Retrieved from: http://www.unn.ru/pages/e-library/methodmaterial/ files/166.pdf.
Baloglu S. (2001). Image variations of Turkey by familiarity index: informational and experiential dimensions. Tourism Management, 22(2), 27-133.
Bigne J.E., Sanchez M.I. & Sanchez J. (2001). Tourism image, evaluation variables and after purchase behavior: inter-relationship. Tourism Management, 22(6), 607-616.
Borg J. (1994). Demand for city tourism in Europe: tour operators' catalogues. Tourism Management, 15(1), 66-69.
Chi C.G.Q., & Qu H. (2008). Examining the structural relationships of destination image, tourist satisfaction and destination loyalty: An integrated approach. Tourism Management, 29(4), 624-636.
Churchill G.A. & Surprenant C. (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing Research, 19(4), 491-504.
Danaher P.J. & Arweiler N. (1996). Customer satisfaction in the tourist industry: a case study of visitors to New Zealand. Journal of Travel Research, 35, 89-93.
Dindia K., & Allen M. (1992). Sex differences in self-disclosure: A meta-analysis. Psychological Bulletin, 112(1), 106-124.
Echtner C.M. & Ritchie J.R.B. (1993). The measurement of destination image: an empirical assessment. Journal of Travel Research, 31(3), 3-13.
Fakeye P.C. & Crompton J.L. (1991). Image differences between prospective, First-time, and repeat visitors to the Lower Rio Grande Valley. Journal of Travel Research, 30(10), 10-16.
Feng R. & Jang S. (2004). Temporal destination loyalty: a structural initiation. Advances in Hospitality and Tourism Research, 9, 207-221.
Floyd M.F., Gibson H., Pennington-Gray L. & Thapa B. (2004). The effect of risk perceptions on intentions to travel in the aftermath of September 11, 2001. Journal of Travel & Tourism Marketing, 15, 19-38.
Floyd M.F. & Pennington-Gray L. (2004). Profiling risk perception of tourists. Annals of Tourism Research, 31(4), 1051-1054.
Fox J. (2005). Linear models, problems. Pp. 515-522 In Kimberly Kempf-Leonard, ed., Encyclopedia of Social Measurement, Vol. 2, (pp. 515-522). Amsterdam: Elsevier.
Fuchs, G. & Reichel, A. (2006). Tourist destination risk perception: the case of Israel. Journal of Hospitality & Leisure Marketing, 14(2), 83-108.
Gartner W. (1989). Tourism image: attribute measurement of state tourism products using multidimensional scaling techniques. Journal of Travel Research, 28(Fall), 16-20.
Gensch D.H. (1978). Image-measurement segmentation. Journal of Marketing Research, 15(3), 384-394.
Gibson H.J., Qi C.X. & Zhang J.J. (2008). Destination image and intent to visit China and the 2008 Beijing Olympic Games. Journal of Sport Management, 22, 427450. Getz, D. (1991). Festivals, special events and tourism. New York, N.Y.: Cognizant Communication.
Gitelson R.J. & Crompton J.L. (1984). Insights into the repeat vacation phenomenon. Annals of Tourism Research, 11, 199-217.
Harrison-Walker L.J. (2001). The measurement of word-of-mouth communication and an investigation of service quality and consumer commitment as potential antecedents. Journal of Service Research, 4(1), 60-75.
Haywood K.M. & Muller T.E. (1988). The urban tourist experience: evaluating satisfaction. Journal of Hospital & Tourism Research, 12, 453-459.
Horner S., Swarbrooke J. (2004) Case study 12 -Tourism in Russia. International cases in tourism management (pp.137-146). Elsevier ButterworthHeinemann: Burlington, USA.
Hui T.K., Wan D. & Ho A. (2007). Tourists' satisfaction, recommendation and revisiting Singapore. Tourism Management, 28, 965-975.
Jang S. & Feng R. (2007). Temporal destination revisit intention: the effects of novelty seeking and satisfaction. Tourism Management, 28, 580-590.
Kaplaidou K. (2009). Relationships among behavioral intentions, cognitive event and destination images among different geographic regions of Olympic Games spectators. Journal of Sport & Tourism, 14(4), 249-272.
Kozak M. (2001). Repeaters' behavior at two distinct destinations. Annals of Tourism Research, 28(3), 784807.
Kozak M. (2002). Measuring comparative destination performance: a study in Spain and Turkey. Journal of Travel & Tourism Marketing, 13(3), 83-110.
Kozak M. & Rimmington M. (1999). Measuring tourist destination competitiveness: conceptual considerations and empirical findings. Hospitality Management, 18, 273-283.
Kuftiryov I.G. (2011). Development of the tourism sector in the Nizhny Novgorod region as the market segment in the region innovation system. Retrieved from: http://www.unn.ru/e-library/methodmaterial.
html?pscience=19.
Lee C.K., Lee Y.K. & Lee B. (2004). Korea's destination image formed by the 2002 World Cup. Annals of Tourism Research, 32(4), 839-858.
Lehto X.Y., Morrison A.M. & O'Leary J.T. (2001). Does the visiting friends and relatives' typology make a difference? A study of the international VFR market to the United States. Journal of Travel Research, 40(2), 201-212.
Lepp A. & Gibson H. (2003). Tourist roles, perceived risk and international tourism. Annals of Tourism Research, 30(3), 606-624.
Litvin S.W. Goldsmith R.E. & Pan B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29, 458-468.
Mano H. & Oliver R.L. (1993). Assessing the dimensionality and structure of the consumption experience: evaluation, feeling, and satisfaction. Journal of Consumer Research, 20(3), 451-466.
Maser B. & Weiermair K. (1998). Travel decision-making: from the vantage point of perceived risk and information preferences. Journal of Travel & Tourism Marketing, 7(4), 107-121.
Milaman A. & Pizam A. (1995). The role of awareness and familiarity with a destination: The Central Florida case. Journal of Travel Research, 33(3), 21-27.
Morgan N.J., Pritchard A. & Piggott R. (2003). Destination branding and role of stakeholders: the case of New Zealand. Journal of Vacation Marketing, 9(3), 285299.
Murphy P., Pritchard M.P. & Smith B. (2000). The destination product and its impact on traveller perceptions. Tourism Management, 21, 43-52.
Oliver R.L. and De Sarbo W.S. (1988), — Response Determinants in Satisfaction Judgments. Journal of Consumer Research, Vol. 14, pp. 495-507.
Oppermann M. (2000). Tourism destination loyalty. Journal of Travel Research, 39(1), 78-84.
Parasurman A., Zeithaml V.A. & Berry L.L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49, 4150.
Peters M. & Pikkemaat B. (2003). Sports and more: a students' image analysis of the city of Innsbruck. 53rd Congress of AIEST in Athens (Greece), 7-11 September, 2003.
Pizam A. (1999). A comprehensive approach to classifying acts of crime and violence at tourism destinations. Journal of Travel Research, 38, 5-12.
Pizam A., Neumann Y. & Reichel A. (1978). Dimensions of tourism satisfaction with a destination. Annals of Tourism Research, 5, 314-322.
Pizam A. & Milman A. (1993). Predicting satisfaction among firs-time visitors to a destination by using the expectancy disconfirmation theory. International Journal of Hospitality Management, 12(2), 197-209.
Pritchard M.P. & Havitz M.E. (2006). Destination appraisal: an analysis of critical incidents. Annals of Tourism Research, 33(1), 25-46.
Reisinger Y. & Mavondo F. (2005). Travel anxiety and intentions to travel internationally: implications of travel risk perception. Journal of Travel Research, 43,212-225.
Ritchie J.R.B. & Smith H. (1991). The impact of a mega-event on host region awareness: a longitudinal study. Journal of Travel Research, 30(3), 3-10.
Roehl W.S. & Fesenmaier D.R. (1992). Risk perceptions and pleasure travel: an exploratory analysis. Journal of Travel Research, 30, 17-26.
Simpson P.M. & Siguaw J.A. (2008a). Perceived travel risks: the traveler perspective and manageability. International Journal of Tourism Research, 10, 315-327.
Smirnova M. (2012). Crime Nizhny Novgorod is increasing. But it does not make police concerned. Komsomolskaya Pravda. Retrieved from: http ://nnov. kp. ru/daily/25848.4/2818156/
Sonmez S. & Graefe A.R. (1998a). Influence of terrorism risk on foreign tourism decisions. Annals of Tourism Research, 25, 112-144.
Sonmez S. & Graefe A.R. (1998b). Determining future travel behavior from past travel experience and perception of risk and safety. Journal of Travel Research, 37, 171-177.
Stepchenkova S. & Morrison A.M. (2008). Russia's destination image among American pleasure travelers: revisiting Echtner and Ritchie. Tourism Management, 28, 548-560.
Tiefenbacher J.P., Day, F.A. & Walton J.A. (2000). Attributes of repeat visitors to small tourist-oriented communities. The Social Science Journal, 37(3), 299308.
Tsaur S., Tzeng G. & Wang K. (1997). Evaluating tourism risks from fuzzy perspectives. Annals of Tourism Research, 24(4), 796-812.
Tse D.K. & Wilton P.C. (1988). Models of consumer satisfaction formation: an extension. Journal of Marketing Research, 25(2), 204-212.
Qu H. & Li I. (1997). The characteristics and satisfaction of Mainland Chinese visitors to Hong Kong. Journal of Travel Research, 35, 37-41.
Um S., Chon K. & Ro Y. (2006). Antecedents of revisit intention. Annals of Tourism Research, 53(4), 11411158.
Wang C. & Hsu M.K. (2010). The relationships of destination image, satisfaction, and behavioral intentions: An integrated model. Journal of Travel & Tourism Marketing, 27(8), 829-843.
Weinberger M.G., Allen, C.T. & Dillon W.R. (1981). Negative information: Perspectives and research directions. Advances in Consumer Research, 8(1), 398-404.
Yoon Y., & Uysal M. (2005). An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tourism Management, 26(1), 45-56.
FACTORS AFFECTING POST-VISITATION BEHAVIOR OF DOMESTIC TOURISTS: A CASE OF NIZHNI NOVGOROD, RUSSIA
G. Simanovskaya, S. Stepchenkova
University of Florida, USA
Nizhni Novgorod is one of eleven Russian cities to host the FIFA World Cup in 2018. The event is expected to increase tourist arrivals to the city, both domestic and international, and brings the attention to the improvement of the city's tourism offer and destination experiences of tourists. The study investigates factors of destination performance, risk perception, familiarity, and tourist type as they affect post-visitation tourist behavior in the context of domestic travel to a large urban destination. The data were obtained in 2013 through an online survey of domestic visitors to Nizhni Novgorod, Russia. Destination performance and concerns associated with travel were found to influence both the intention to revisit and the willingness to recommend the city in social networks as well as offline. The results of the study may aid in strategizing tourism development in Nizhni Novgorod, identifying areas for resource allocation, and positioning Nizhni Novgorod among other historic Russian cities in the European part of the country.
Keywords: destination performance, domestic tourists, Nizhni Novgorod, online survey, post-visitation behavior, risk perceptions, urban destination.
