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Article

Destination Personality, Destination Image, and Intent to Recommend: The Role of Gender, Age, Cultural Background, and Prior Experiences

by
WooHyuk Kim
1,*,
Kristin Malek
1,
NamJo Kim
2 and
SeungHyun “James” Kim
3
1
Department of Hospitality Management , Kansas State University, KS 66506, USA
2
School of Tourism, Hanyang University, Seoul 04763, Republic of Korea
3
The School of Hospitality Business, Michigan State University, MI 48824, USA
*
Author to whom correspondence should be addressed.
Sustainability 2018, 10(1), 87; https://doi.org/10.3390/su10010087
Submission received: 4 December 2017 / Revised: 25 December 2017 / Accepted: 28 December 2017 / Published: 31 December 2017
(This article belongs to the Special Issue Challenges and Opportunities for Sustainable Tourism)
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Versions Notes

Abstract

When tourists chose destinations, they usually select locations that satisfy the subjective criteria of their requirements. The purpose of this study was to delineate those criteria by analyzing the interrelationships among destination personality, image, and intent to recommend while examining the effects of gender, age, cultural background, and prior tourist experience. The data were collected from a major tourism destination in South Korea. A total of 316 usable surveys were analyzed using structural analysis. The results show that three of the four factors for destination personality significantly affected destination image. In turn, destination image influenced intent to recommend. Subsequent tests for metric invariances showed differences in the moderating role of cultural background, gender, age, and prior experience.

1. Introduction

Due to a steady increase in global tourism, today’s marketers are having to find cutting-edge ways to highlight their destination. Government officials and destination marketing organizations (DMOs) have to utilize strong branding initiatives to attract more visitors and investors [1]. These agencies and other advertising executives must create and distinguish the images of their destination against others to gain a competitive edge. Despite this need to stand apart, similar attributes are often promoted in all destination marketing and therefore no longer help to differentiate a destination from their competitors [2].
Organizations have started to create brand personalities for their products. Brand personality refers to a set of human characteristics that are attributed to that brand name [3]. This created personality is something that consumers relate to and feel strongly about. This personality is often tied directly to the target market’s personality. For example, think about the brand personalities of Harley Davidson versus Dove. The former is more rugged and macho, the latter more sincere and feminine. This is an important concept for destinations and should be applied and studied more rigorously. Similar to products, categorizing destinations based on their functional attributes makes them easily interchangeable. Easily interchangeable functional descriptors are not going to differentiate a destination from others and, therefore, other methods must be utilized. One of these methods is creating a destination personality. Ekinci and Hosany [4] suggested that creating a destination personality includes establishing unique destination brands, understanding visitors’ perceptions of these locations, and crafting a distinctive identity. Destination marketers have started using a combination of destination personality and image to differentiate themselves from competing brands successfully [5]. Destination personality should not be confused with destination image. Destination personality is the tourism office’s branding of the destination utilizing human characteristics, whereas destination image is a person’s view of that destination.
Destination image formation is influenced by many factors, which are often not analyzed together in a single study. Brand personality is just one of these factors, however critics state that the definition of brand personality is broad and embraces characteristics that are not directly related to personality [6,7].
Destination personality and destination image can lead to increased intent to recommend. Understanding tourists’ behavioral intentions is significant because it serves as the basis of competitive advantage and sustainability of the destination [8]. Due to increasing competition, and recognizing the importance of loyal tourists, tourists’ behavioral intentions has become a critical part of destination marketing research [9]. Despite this increase in research, it is relatively rare for scholars to study the link between brand personality and tourists’ behavioral intentions factors directly [10].
One key differentiator in this study from previous studies is the target destination size. Oftentimes entire countries or states are analyzed for destination image or destination personality studies [11]. This is a large oversight, as separate regions or districts within one country or state can have distinct personalities. In the United States and other countries, different regions have their own distinct speech and word choice, foods, sub-cultures, history, and physical terrain. This particular study sought to examine a strongly branded district to see if the results are different from research analyzing entire states or countries. Therefore, a strongly branded district in South Korea, “Gangnam”, was chosen due to its high profile and strong brand. This area is known as the “Beverly Hills of Seoul” for its high-end fashion, fine dining, boutiques, and trendy restaurants [12]. It received worldwide recognition due to Psy’s 2012 mega-hit song, “Gangnam Style”.
Another key contribution of this research is the inclusion of moderating variables. Other factors that have been found to impact destination image are the cultural background of the tourists [13] and prior tourist experience which can influence behavior and shape intentions [14]. Other studies have also identified significant differences in destination image between tourists based on their nationality [15]. Therefore, these variables are analyzed in this study. Although some prior tourist studies have explored the relationships among socio-demographic variables, nationality, age, gender, and destination choices (e.g., [16,17,18]), there have been mixed empirical results concerning these variables. Therefore, this study includes them for further analysis.
The purpose of this study is to explore the relationship among destination personality, image, and the tourists’ behavioral intentions. This study investigated the perceived destination personality of a strongly branded district and its underlying dimensions. The researchers also examined how differences in tourists’ genders, ages, cultural background, and prior experiences affected the relationships between destination personality and destination image. Figure 1 provides our proposed research model. The present study advances the theoretical understanding of the effects of socio-demographic variables on these relationships. The study also contributes to the development of strategic destination marketing using market segmentation.
The study proceeds as follows. The following section discusses the theoretical framework and introduced the hypotheses. Then, the methodology is analyzed in detail and the results are presented. Finally, this study discusses theoretical and practical implications, limitations and future research directions.

2. Literature Review

2.1. Destination Personality

Brand personality has been defined as the set of human characteristics associated with a brand [19]. In other words, consumers can view brands as possessing humanlike traits, which is a valuable concept for characterizing the personal qualities that drive purchase behavior and use [20]. Consumers are more inclined to buy the products with which they can personally identify [19]. This is directly transferable to destinations. Effective marketing and management of a destination personality can help consumers develop a favorable image of that location [21]. This concept has strong ties to BrandSelf Congruity Theory [22,23]. This theory states that consumers tend to favor brands for their symbolic qualities rather than their cognitive qualities [24]. This means that the more positive symbolic mind frame that tourists associate with a destination, the more likely they will be to visit it.
Advertising can be impactful in the development of brand personality as a marketing tool. Within the travel and hospitality context, destination personality is vital to making a locale more competitive [11]. To manage the perceptions that tourists have and contribute to the development of a unique identity, destinations can be branded through careful management of their destination personality [25].
Aaker [19] conducted the foundational study which applied the concept of brand personality to tourism contexts, which is now a commonly accepted belief that tourist destinations can have personalities and be marketed as brands [4]. Specific to destinations, brand personality can also be associated with the set of unique and favorable associations and memories that tourists have connected to a particular place [3]. Since then, several studies have investigated the role of destination personality in evaluating scale development (e.g., [4,26,27]) and tourists’ behavioral intentions (e.g., [5,9,11,28,29,30]). The original scale was Aaker [19] research which established the foundational theoretical framework of the brand personality construct utilizing 42 items. These 42 items resulted in five distinct dimensions: sincerity, excitement, competence, sophistication, and ruggedness. Later, Aaker, et al. [31] completed a similar study that found the first four dimensions to be identical but replaced ruggedness with peacefulness. Other studies that utilized this scale have found somewhat similar results. Ekinci and Hosany [4] found dimensions of sincerity, excitement, and conviviality. Kim and Lehto [32] found seven dimensions: excitement, competence, sincerity, sophistication, ruggedness, uniqueness, and family orientation. Hultman, et al. [33] found six dimensions: excitement, sophistication, activeness, dependability, philoxenia, and ruggedness. Gómez Aguilar, Yagüe Guillén and Villaseñor Roman [25] explored the dimensions in Spain and found five dimensions: sincerity, excitement, competence, sophistication, and ruggedness. Table 1 provides a cross comparison of existing tourism literature utilizing this scale. Although marketing scholars have accepted Aaker’s five dimensions of brand personality, it must be noted that the pattern and content of the dimensions in service contexts are not always identical to those found in the marketing field [34].

2.2. Destination Image

Destination personality should not be confused with destination image. Destination personality is the tourism office’s branding of the destination utilizing human characteristics, whereas destination image is a person’s view of that destination. Apostolopoulou and Papadimitriou [11] examined the relationship linking destination personality and destination image and found that destination personality does influence the destination image, but the two are distinctly different concepts [35]. Destination image plays an important role in tourists’ decision-making processes and subsequent travel behavior [7,37]. Destination image has been used to make cognizable an individual’s opinions and impressions about a destination, which together signify its holistic descriptions in that tourist’s mind [11,38].
Although an extensive literature base has developed conceptualizing and measuring destination image, the studies themselves have shown mixed results (e.g., [39,40,41]). The majority of extant studies consider destination image as a multidimensional idea with two key components. These dimensions are the tourist’s: (1) cognitive evaluations; and (2) affective evaluations of a place, which together form the tourist’s general image [7,42]. Given the wealth of choices prospective tourists enjoy when planning their travels, the destination images those future customers hold will be crucial to their decision making—and, hence, to destination marketers’ success or failure.
The discussion of destination image has largely revolved around national-level branding with DMOs successfully creating sustained image-sets for countries like France, Great Britain, Jamaica, and others [11,43]. However, for true understanding and application of destination brand development, it is likely that small-scale tourism locales such as cities and districts may provide more fruitful results. Districts are often previously unbranded in tourists’ minds, with few existing associations and attributes, meaning new district destination images can be implanted easily.

2.3. The Relationships Among Destination Personality, Image, and Intent to Recommend

Destination image and personality are different but related concepts [28,35]. Ekinci and Hosany [4] have provided empirical evidence that destination personality plays a key role in influencing destination image formation. Moreover, Murphy, Moscardo and Benckendorff [30] also found that, while personality may play a central role in destination image creation, a strong personal link with the personality of a destination does not directly convert into visitation. It remains crucial that destinations project strong positive qualities to entice visitation, with characteristics like excitement, sincerity, comfort, and activity helping to create an attractive image.
In addition, destination image has been found to play a significant role in predicting tourists’ behaviors [44,45]. The relationship between image and intent to recommend has been shown to be statistically significant in several studies (e.g., [11,46]). These studies found that destination image has a positive influence on intent to recommend. Based on all of the cited literature, the following hypotheses are proposed:
Hypotheses 1 (H1a).
The destination personality trait of excitement has a positive influence on destination image.
Hypotheses 1 (H1b).
The destination personality trait of sincerity has a positive influence on destination image.
Hypotheses 1 (H1c).
The destination personality trait of comfort has a positive influence on destination image.
Hypotheses 1 (H1d).
The destination personality trait of activeness has a positive influence on destination image.
Hypotheses 2.
Perceived overall destination image has a positive influence on intention to recommend.

2.4. Market Segmentation in the Destination Literature: Socio-Demographic Variables

Researchers have previously questioned whether the concept of brand personality is valid, reliable, and generalizable enough to be useful across various consumer segments [31]. It is true that market segmentation allows DMOs and government officials to understand tourists’ needs and expectations for their destination [47].
In the tourism literature, some studies have examined the relationship between socio-demographic variables and segmentation. These variables include cultural differences (e.g., [48]), age (e.g., [49,50]), gender (e.g., [51]), and demographics (e.g., [18,52]). For example, along with gender, a traveler’s age has been found to play a key role in the formation of destination image [51]. Due to the ongoing debate around the importance of socio-demographic factors, it has been said that further studies are needed [53]. Studies on gender and age differences lack overall in destination personality and destination image research. These variables’ influence on the formation of intent to recommend in the context of tourism remains unclear.
Extant research has established that culture can play a significant role in overall brand perceptions [48,54]. Aguirre-Rodriguez [13] found that consumers in a variety of cultural contexts identify with different culturally relevant brand personality traits. Aaker, Benet-Martínez and Garolera [31] research led to the emergence of a set of brand personality dimensions that have comparable meanings in both Japan and the United States, as well as other dimensions that carry more specific cultural associations. However, some scholars claim that cross-cultural differences in destination personality have not sufficiently been investigated [39,55,56].
Prior experience with a destination can also play a key role in the perception of that destination [57]. Some studies have found that prior experience has influenced tourist behaviors [14,27]. Past travel experience may also significantly influence destination image formation [58]. However, there is still a lack of understanding about the relationship among destination personality, destination image, and intention to recommend with socio-demographic variables in a systematic and all-inclusive framework [59]. Based on this need, the following hypotheses will be explored:
Hypotheses 3 (H3a).
Cultural background significantly moderates the relationship between the destination personality trait of excitement and destination image.
Hypotheses 3 (H3b).
Cultural background significantly moderates the relationship between the destination personality trait of sincerity and destination image.
Hypotheses 3 (H3c).
Cultural background significantly moderates the relationship between the destination personality trait of comfort and destination image.
Hypotheses 3 (H3d).
Cultural background significantly moderates the relationship between the destination personality trait of activeness and destination image.
Hypotheses 4 (H4a).
Gender significantly moderates the relationship between the destination personality trait of excitement and destination image.
Hypotheses 4 (H4b).
Gender significantly moderates the relationship between the destination personality trait of sincerity and destination image.
Hypotheses 4 (H4c).
Gender significantly moderates the relationship between the destination personality trait of comfort and destination image.
Hypotheses 4 (H4d).
Gender significantly moderates the relationship between the destination personality trait of activeness and destination image.
Hypotheses 5 (H5a).
Age significantly moderates the relationship between the destination personality trait of excitement and destination image.
Hypotheses 5 (H5b).
Age significantly moderates the relationship between the destination personality trait of sincerity and destination image.
Hypotheses 5 (H5c).
Age significantly moderates the relationship between the destination personality trait of comfort and destination image.
Hypotheses 5 (H5d).
Age significantly moderates the relationship between the destination personality trait of activeness and destination image.
Hypotheses 6 (H6a).
Prior travel experience significantly moderates the relationship between the destination personality trait of excitement and destination image.
Hypotheses 6 (H6b).
Prior travel experience significantly moderates the relationship between the destination personality trait of sincerity and destination image.
Hypotheses 6 (H6c).
Prior travel experience significantly moderates the relationship between the destination personality trait of comfort and destination image.
Hypotheses 6 (H6d).
Prior travel experience significantly moderates the relationship between the destination personality trait of activeness and destination image.

3. Methods

3.1. Study Settings: Tourism Destinations at a District Level

Although destination marketing research has increased significantly over the past two decades, the majority of previous studies have focused on destinations at the country or state/provincial level [11,40,43]. However, it is possible that districts, cities, and regions can have distinctly different characteristics and brands within the same country or state [60], especially if these locations have strong identities [11]. In the United States, tourists (and even citizens) view Washington DC, New York City, and New Jersey as having distinct and contrasting identities despite their mutual proximity. Within the area of New York City alone, areas such as Central Park, Long Island, Brooklyn, and others conjure different images in visitors’ minds. This phenomenon reveals an important research gap: a lack of research at the district, city, and regional areas that need further investigation [11].
These differences in destination image at a more refined level are not just true in the United States. As stated earlier, this study focuses on a very distinct district internationally known for its high-end fashion, the Gangnam district in South Korea. The Gangnam district has become a major tourist destination associated with upscale and diverse culture [12]. Gangnam is a strong branded destination. Although any one study at a district level may not be entirely generalizable, it is vital to continue to study a broad range of districts, cities, regions, states, and countries to be able to accurately identify the real foundational variables that contribute to destination personality, image, and intention to recommend. This study hopes to contribute to the understanding of this relationship more clearly at this more focused branded-district level.

3.2. Measurement Scales

The measurement items utilized in this research were adapted from the existing literature with the wording modified for the present study’s setting. Destination personality was measured with 20 items adapted from Ha [21], Hosany, Ekinci and Uysal [35], and Usakli and Baloglu [5]. In terms of image, this study focuses on tourists’ perceived destination image. Destination image was measured by four items drawn from three different prior studies and customized for this research [7,40,45]. For example, “The activity of Gangnam is diverse”. Intent to recommend was measured by three items from established scales subsequently modified for this study [17,61]. For example, “I would recommend that others visit Gangnam”. All items were evaluated using a seven-point Likert scale ranging from very strongly disagree (1) to very strongly agree (7). The survey also included questions related to socio-demographics and aspects of the respondents’ travel behaviors. Prior to data collection, a pilot test was conducted to assess the internal consistency of each construct with participants recruited from an online research company (n = 30). Survey items were also pre-tested for clarity, accuracy, and readability.
To check any potential common method variance (CMV), Harman’s single-factor test was used [62]. Typically, to check CMV, this test requires loading all study variables in an exploratory factor analysis (EFA). According to the EFA results, these results showed that the first factor consists of 39.1% of the total variance. These results indicated that there was not an issue of common method variance.

3.3. Data Collection

University students were recruited and trained to conduct the survey onsite. The researchers instructed the students in the administration process and interview technique, and gave them a brief description of the research purpose. This research team surveyed international tourists in the COEX mall, a large convention facility, underground shopping mall, and transportation hub in the Gangnam district of Seoul. All completed questionnaires were returned onsite. After completion of the survey, small incentives in the form of Korean souvenirs were given to the participants to compensate them for their time. A field survey with a non-probability convenience sampling approach was chosen as the most efficient data collection method. Incomplete surveys were excluded in their entirety resulting in no missing data points in the results. The sample size of over 300 satisfies the minimum sample size threshold for structural equation modeling [63].
Table 2 presents a complete demographic profile of the study’s participants. A total of 371 international tourists responded to the survey. To ensure a meaningful sample, Korean citizens were not surveyed and only foreign visitors to the Gangnam area were asked to take part. Of those 371, 55 returned missing or incomplete responses and were deleted, resulting in 316 valid responses remaining for analysis. According to the results of the demographic data, the majority of those sampled were 21 to 30 years old (48.4%). Approximately 48.1% were male and 51.9% were female. A high percentage of the participants held a bachelor’s degree (44.3%). When asked about their reasons for traveling, 40.2% of the respondents said that it was for leisure/vacation purposes. The sample consisted of 128 Easterners (Japanese, Chinese, etc.) and 188 Westerners (Americans, Canadians, etc.)

3.4. Data Analysis

Data were examined using the SPSS and SPSS Amos 21.0 programs. First, descriptive statistics were evaluated to define the demographic profile. Exploratory factor analysis (EFA) was then used to discover the underlying structure of the destination personality scale in respondent groups, followed by confirmatory factor analysis (CFA) to test the suitability of the measurement model and to check that the indicator variables (i.e., items in destination personality, destination image, and intent to recommend) were indeed determining the constructs of interest. CFA was undertaken to confirm the dimensionality of the constructs. The convergent and discriminate validities of the factor structure were evaluated using CFA. Lastly, path and multiple group analyses in SEM were conducted to study the hypothesized relationships among constructs. In accordance with the literature, a number of indicators were used to measure the model fit [64], including the Chi square test, root mean square error of approximation (RMSEA), comparative fit index (CFI), and normalized fit index (NFI).

4. Results

4.1. Hypotheses Testing: Dimensionality of Destination Personality

To run SEM effectively with a maximum likelihood estimation, the data should have a multivariate normal distribution, as non-normality might inflate the chi-square (χ2) value and underestimate the fit indices [65]. Multivariate non-normality was rejected (Kurtosis = 76.651, critical ratio (CR] = 25.059) and the study utilized bootstrapping. Bootstrapping is the practice of estimating properties of an estimator by measuring the properties when sampling from an approximating distribution [66]. This is a good way to measure parameter estimates accurately and is asymptotically more accurate than the standard intervals obtained using sample variance and assumptions of normality [67]. This study performed 2000 bootstrap measurements based on the 316 original samples. Discriminate validity was also assessed. Table 3 provides the correlation estimates. Correlations between constructs were not excessively high, and none of the pairs for the 95% confidence interval approached 1.00, thus providing support for discriminate validity [68].
The proposed structural model adequately fits the data: χ2 = 443.3 (df = 156, p < 0.001), χ2/df = 2.84, CFI = 0.91, RMSEA = 0.56, and NNFI = 0.90. The results revealed that destination personality was positively influenced by three of the four factors of destination image: excitement (H1a: β = 0.352, p < 0.05), comfort (H1c: β = 0.584, p < 0.05), and activeness (H1d: β = 0.159, p < 0.05). Therefore, Hypotheses 1a,c,d were supported. However, Hypothesis 1b (sincerity) was not supported. Comfort was found to be the most influential personality dimension affecting overall image. Furthermore, the results supported Hypothesis 2 as overall destination image was found to influence intent to recommend positively (β = 0.751, p < 0.05).

4.2. Multiple-Group Analysis—Measurement Invariance Test

As shown in Table 4, all factor loadings for the observed variables that were measured on the same construct were statistically significant, which demonstrates that they effectively measured their corresponding factors. This data supports the convergent validity of the results. All observed variables that were specified to measure each of the constructs in the measurement model have relatively high loadings (p < 0.05), which ranged from 0.56 to 0.91. Additional testing revealed that the AVEs in all constructs exceeded the critical level of 0.05. This demonstrates that both indicators are evidence of convergent validity.
Prior to group comparisons of construct means and construct relationships, a measurement invariance test in multiple group analysis was conducted (e.g., [69]) to determine whether obtained factor loadings in the measurement model are indifferent across the two groups in Table 5. Tests of invariance involve a comparison of nested models and, in this analysis, two models were tested (labeled A and B in Table 6). Two series of multiple group invariance analyses were done separately to see whether factor loadings were invariant across two groups. Cheung and Rensvold [70] recommend examining the change in CFI and state that a change of 0.01 or less indicates that the invariance hypothesis should not be rejected. Both models were found to have good overall fit to the data. More importantly, the CFI remained unchanged across models, proving support for the factor loadings and construct mean invariance Cheung and Rensvold [70].

4.3. Structural Relationships Across Groups

To test the moderating function across groups (cultural background, gender, age, and prior experience), the study utilized a multiple-group analysis. Figure 2 shows the final structural model results. The moderating function of cultural background was then analyzed between all four factors of destination personality and destination image. Table 7 provides the results of the multiple group path analysis. All model fit indices fell within the recommended range and all hypothesized effects were statistically significant except for the paths from sincerity (SIN) to destination image (DI) and from activeness (ACT) to destination image (DI) in both the Western and Eastern groups. All statistically significant relationships moved in their hypothesized directions. In terms of effect size, comfort (COM) demonstrated the highest effect on destination image (DI) in the Western market (β = 0.64, t = 7.44, p < 0.05). In contrast, the effect of excitement (EXC) was the highest in the Asian market (β = 0.51, t = 6.92, p < 0.01). Destination image (DI) explained 80% and 75% of the variance in the Western and Eastern markets, respectively. The explained variances of intent to recommend were 64% in the Western market and 62% in the Eastern market. Moreover, destination image (DI) had a strong effect on intention to recommend (INR) among both groups (Western: β = 0.80, t = 9.17, p < 0.01; Asian: β = 0.86, t = 8.61, p < 0.01). A chi-square (χ2) difference test was used to test group differences on individual paths. Table 6 presents the results for the path coefficients. Chi-square difference tests showed that the paths from excitement (EXC) to destination image (DI), from comfort (COM) to destination image (DI), and from destination image (DI) to intent to recommend (INR) were statistically significant: Δχ2 (1) = 6.10, p < 0.01, Δχ2 (1) = 6.07, p < 0.01 and Δχ2 (1) = 3.85, p < 0.05. These results demonstrate that differences exist in the four paths across the samples. However, no statistically significant differences were revealed for paths from other links. In summary, similar to gender and age, Hypotheses 3a,c were supported, whereas Hypotheses 3b,d were not supported.
To test Hypotheses 4–6, a chi-square (χ2) difference test was used to categorize the differences of individual paths. Figure 2 shows the results of the final structural model. The moderating function of gender in the relationship between destination personality (excitement) and destination image was found to be significant (χ2 = 6.2 > χ2 0.05(1) = 3.84, df = 1). However, gender’s effect between destination personality (sincerity) and destination image was not significant (χ2 = 0.1 < χ2 0.05(1) = 3.84, df = 1). The gender effect between destination personality (comfort) and destination image, similar to excitement, was found to be significant (χ2 = 4.8 > χ2 0.05(1) = 3.84, df = 1). Finally, gender’s effect between destination personality (activeness) and destination image, similar to sincerity, was found not to be significant (χ2 = 0.2 < χ2 0.05(1) = 3.84, df = 1). In summary, Hypotheses 4a,c were supported, whereas Hypotheses 4b,d were not supported.
Next, the moderating function of age was analyzed between all four factors of destination personality (excitement, sincerity, comfort, and activeness) and destination image. For excitement, the difference in chi-square and value was found to be significant (χ2 = 16.1 > χ2 0.05(1) = 3.84, df = 1). However, age was found to be not significant between destination personality (sincerity) and destination image (χ2 = 1.4 < χ2 0.05(1) = 3.84, df = 1). Next, similar to excitement, the age effect between destination personality (comfort) and destination image was found to be significant (χ2 = 4.3 > χ2 0.05(1) = 3.84, df = 1). However, like sincerity, between destination personality (activeness) and destination image, age was found not to be significant (χ2 = 1.3 < χ2 0.05(1) = 3.84, df = 1). In summary, Hypotheses 5a,c were supported, whereas Hypotheses 5b,d were not supported. This finding is similar to the results derived for gender.
Finally, the moderating function of prior experience was analyzed between all four factors of destination personality and destination image. For excitement, the difference in chi-square and value was found not to be significant (χ2 =1.5 < χ2 0.05(1) = 3.84, df = 1). In addition, prior experience’s effect between destination personality (sincerity) and destination image was found not to be significant (χ2 = 1.2 < χ2 0.05(1) = 3.84, df = 1). However, the prior experience effect between destination personality (comfort) and destination image was found to be significant (χ2 = 5.3 > χ2 0.05(1) = 3.84, df = 1). Finally, between destination personality (activeness) and destination image, prior experience was found not to be significant (χ2 = 1.5 < χ2 0.05(1) = 3.84, df = 1). In summary, this means Hypotheses 6a,b,d were not supported, but Hypothesis 6c was supported. This finding differs from previous moderators’ results wherein the path between excitement and image was found to be significantly affected by the moderator. None of the moderators had a significant impact on the paths between sincerity and image or activeness and image.

5. Discussion and Conclusions

Destinations are competing more intensely than ever before to attract visitors and the empirical research exploring the drivers of this phenomenon has increased. While the traditional destination personality concept has been widely recognized, relatively few researchers have examined the relationships among destination personality, destination image, and intent to recommend with socio-demographic characteristics through a systematic framework. The purpose of this study, therefore, was to investigate the perceived destination personality of a branded district and empirically examine the relationship between these variables. To test the proposed moderating impacts of cultural background, gender, age, and prior experience, the researchers conducted an invariance test on the models.
The study findings align with that of previous studies showing the essential role of destination personality in forming destination image [11,28,35]. In this research, destination personality is modeled through four dimensions: sincerity, excitement, comfort, and activeness. These dimensions have been found throughout the previous literature. The findings regarding the influence of the Gangnam district’s destination personality are particularly interesting. In this study, sincerity and activeness did not play a role in impacting destination image. Thus, it would be wise for marketers to emphasize the other attributes of excitement and comfort to entice potential visitors. This makes sense if you think about the target market of high end fashion. Typically, the target market is people that enjoy the calmness of walking around stores, window shopping, trying things on, and the exciting moments of finding the perfect things that work for them. In other words, comfort and excitement. Fashion is often seen as “shallow” and not in-depth or sincere and not very strenuous or active. These results offer important implications for how to go about marketing tourist destinations that are similar to this high-fashion district.
A multiple-group analysis revealed key differences between Western and Eastern tourists. In particular, Western tourists rated comfort much higher than Eastern travelers. In contrast, Eastern tourists rated excitement more highly than Western tourists. Some researchers claim that the link between image and intention to recommend is inconclusive [71]. Nonetheless, these findings support such a link. In terms of gender, it was interesting that male respondents rated excitement higher than female respondents, who were more likely to associate the high-end fashion district with comfort. The researchers had anticipated female respondents would find this district more exciting because of the high levels of shopping and entertainment (e.g., cosmetics, pop music, etc.). Respondents older than 31 rated desire for excitement slightly higher than the under 31 group; this was also an interesting finding. Additionally, the former group rated comfort higher than the under 31 group. These are important factors to consider: DMOs should utilize these results to provide tangible attributes that will more likely appeal to specific target markets.

5.1. Theoretical Implications

From a theoretical perspective, four dimensions of destination personality emerged from this study, which indicates a partial replication of the framework from Aaker [19]. This finding supports Ekinci and Hosany [4] argument that Aaker [19] brand personality scales may not represent all personality traits that are associated with tourism destinations. It also supports the notion that destination personality cannot be treated uniformly for every destination, and that destination personality might go beyond the commonly acknowledged five dimensions originally identified by Aaker [19].
According to self-congruity theory, the degree of congruence between destination and visitor self-consistency may influence behavior intentions [22,24]. Consistent with this concept, this study found that destination personality influenced a traveler’s intent to recommend. Additionally, while there are existing studies that have analyzed the effect of destination image on destination personality [35], this study examined the reverse [11] and found a connection between destination personality and destination image. Identifying and understanding key attributes of districts in terms of destination personality is critical to the development of the tourism industry.
It is now clear that cultural background plays a key role in brand personality traits [13] and should be included in all future theoretical models. Matzler, Strobl, Stokburger-Sauer, Bobovnicky and Bauer [48] previously investigated the relationships among brand personality, self-congruity, and behavioral intention. However, this study’s results suggest that destination image is also to be considered in these relationships to understand visitors’ perceptions more completely.
Lastly, in terms of target market segmentation, this study found that a traveler’s gender, age, and previous experiences have a positive influence on his or her image of a destination. In other words, the inclusion of gender, age, and previous experience as part of the theoretical framework develops a clearer understanding of the loyalty generation process. These results should help researchers expand existing theoretical frameworks related to leisure travelers’ loyalty and decision formation.

5.2. Managerial Implications

From a practical standpoint, this research identified four significant dimensions of brand personality: sincerity, excitement, comfort, and activeness. As such, this study provides insights that could be particularly helpful for branding and promoting a destination that focuses on high fashion. According to these findings, destination branding strategies that emphasize excitement and activeness components such as events, festivals, and attractions can serve as marketing stimuli for tourists who seek excitement and want to experience vibrant local culture. High end fashion districts should also promote their unique products and modern technology. It is the local identity of the city, reflecting a composite of residents’ day-to-day lives, which could draw tourists. With regard to the link of comfort and destination image, tourists may wish to have a relaxing experience as an outlet to relieve stress. This could vary by an individual in what they find comforting, but shopping, spas, performances, or attractions could satisfy this link.
Locals are an important stakeholder group who can build a stronger destination image for their city [72]. Despite the increase in brand personality research of non-Western societies [31], few studies have been conducted to examine this unique element in connection with foreign tourists to Asian cities. Seoul’s economy is one of the fastest growing in the world and has emerged as a significant consumer market. As this study investigated foreign visitors’ perceptions of a target district in Seoul, the researchers believe the findings will be helpful for creating marketing strategies to differentiate Asian cities and enhance their drawing power.
To categorize tourist markets efficaciously, DMOs must consider how the demographic aspects of gender, age, cultural background, and previous experience affect travel behavior, attitudes [59]. They should develop customized marketing strategies for each target market. The Gangnam district is a complex and unique area in which traditional and modern cultures coexist. DMOs and district officials should consider diverse channels to show what this location has to offer in terms of exciting, unique, and emotional experiences. Such marketing can be particularly effective in helping visitors find the meaning and experiences they seek in a modern urban destination. Such promotional materials can also help to distinguish this destination from others and provide a sustainable competitive advantage.

5.3. Limitations and Future Research

This research has several limitations. Although this research will most likely be generalizable to other high-end fashion districts, these results may not be generalizable to all destinations and cultures. Future studies with wider, larger, and more varied sampling could reveal other differences. The survey included only a limited sample of culture. Future scholars could investigate additional external and internal factors of tourists’ behavioral intentions for creating destination loyalty, which could lead to further conceptual refinement and extensions. These future researchers could include moderating variables such as psychological characteristics, place attachment, or level of familiarity with a destination. Mediators such as satisfaction could be examined for their relationships among these constructs.
Future research could divide destination image into its cognitive, affective, and conative (i.e., impulsive) components. The cross-sectional nature of the data in this study limits our ability to draw strong inferences about the sequence of effects; qualitative approaches could be employed in future research to generate a more comprehensive understanding of the vital element known as destination personality.

Author Contributions

WooHyuk Kim designed and developed the idea of the paper. WooHyuk Kim reviewed related previous research and analyzed the data. All authors wrote and reviewed the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Proposed Research Model.
Figure 1. Proposed Research Model.
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Figure 2. Final Structural Model Result.
Figure 2. Final Structural Model Result.
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Table 1. Destination Personality Traits.
Table 1. Destination Personality Traits.
Author (s)Study AreaDestination Personality Trait
Ekinci and Hosany [4]Three UK cities and one European airportSincerity
Excitement
Conviviality
Hosany, et al. [35]United KingdomSincerity
Excitement
Conviviality
Murphy, Moscardo and Benckendorff [30]North QueenslandSincerity
Excitement
Sophistication
Usakli and Baloglu [5]Las VegasSincerity
Sophistication
Vibrancy
Competence
Contemporary
Apostolopoulou and Papadimitriou [11]GreeceSincerity
Excitement
Kim and Lehto [32]South KoreaSincerity
Excitement
Sophistication
Competence
Ruggedness
Kim and Stepchenkova [36]South KoreaSincerity
Excitement
Sophistication
Competence
Ruggedness
Uniqueness
Peacefulness
Traditionalism
Gómez Aguilar, Yagüe Guillén and Villaseñor Roman [25]SpainSincerity
Excitement
Competence
Sophistication
Ruggedness
Table 2. Respondents’ Demographic Profiles (n = 316).
Table 2. Respondents’ Demographic Profiles (n = 316).
CharacteristicsFrequency%
Gender
Male15251.9%
Female16448.1%
Age
Under 21278.5%
21 to 3015348.4%
31 to 408526.9%
41 or older5111.7%
Nationality
Western18859.5%
Eastern12840.5%
Education Level
High school or less4213.3%
Some college4614.6%
Bachelor’s degree14044.3%
Graduate degree8827.8%
Main purpose for trip
Leisure vacation12740.2%
Meeting or event278.5%
Friends or family299.2%
Business trip7624.1%
Other5718.0%
Table 3. Correlations Estimates, Means, and Standard Deviations (N = 316).
Table 3. Correlations Estimates, Means, and Standard Deviations (N = 316).
123456MSDSQR of AVE
1. EXC1 3.810.530.83
2. SIN0.761 3.890.530.84
3. COM0.630.561 3.510.600.73
4. ACT0.270.210.591 3.260.710.77
5. DI0.750.740.520.341 3.810.630.77
6. INR0.700.630.590.450.7813.870.550.87
Note: EXC = excitement; SIN = Sincerity; COM = Comfort; ACT = Activeness; DI = Destination image; INR = Intention to Recommend; SQR = square root.
Table 4. Confirmatory Factor Analysis Results.
Table 4. Confirmatory Factor Analysis Results.
Constructs and Items Western (n = 188)Asian (n = 128)
Excitement (EXC)
Up-to-dateLoadings a0.6000.813
Successful 0.7840.758
Trendy 0.7920.711
Cool 0.6350.859
Reliability0.8330.842
AVE b0.560.58
Sincerity (SIN)
HonestLoadings0.7010.777
Family oriented 0.9550.831
Sincere 0.8840.535
Down-to-earth 0.5640.569
Reliability0.8100.815
AVE0.510.53
Comfort (COM)
RefreshingLoadings0.7340.793
Humane 0.7820.777
Natural 0.7860.699
Comfortable 0.6830.647
reliability0.8140.825
AVE0.530.54
Activeness (ACT)
DynamicLoadings0.5770.670
Inquiring 0.7820.782
Lively 0.9110.763
Reliability0.7650.768
AVE0.530.51
Destination Image (DI)
Gangnam has good accommodationsLoadings0.7290.788
Gangnam has delicious local food 0.7930.721
The activity of Gangnam is diverse 0.8720.864
Gangnam is a clean place 0.6290.670
Reliability0.8240.839
AVE0.560.57
Intention to Recommend (INR)
I would recommend that others visit this destinationLoadings0.8010.856
I would probably visit this destination in the future 0.8460.823
I would say positive things about this destination to others 0.7050.838
Reliability0.8420.853
AVE0.5810.593
Fit indicesχ2 (df)489.5(189)458.8(189)
χ2/df2.592.43
CFI0.9290.948
RMSEA0.0610.051
Note: a Standardized factor loadings were all significant at p < 0.001. b Average variance extracted; EXC = excitement; SIN = Sincerity; COM = Comfort; ACT = Activeness; DI = Destination image; INR = Intention to Recommend.
Table 5. Multiple Group CFA Analysis: Measurement Invariance Test.
Table 5. Multiple Group CFA Analysis: Measurement Invariance Test.
Modelχ2dfCFIΔχ2 (df)ΔCFIp
A: Hypothesized model (unconstrained)12513780.906---
B: Factor loadings, variances, and covariances, plus error covariances constrained equal15634420.911311.80.06ns
Table 6. Multiple Group Path Analysis: Invariance Test for Path Coefficients.
Table 6. Multiple Group Path Analysis: Invariance Test for Path Coefficients.
χ2
PathUnconstrained a (df = 438)Partially Constrained b (df = 439)Δχ2 c
EXC → DI1500.381500.496.10 *
SIN → DI1500.381500.430.05
COM → DI1500.381500.466.07 *
ACT → DI1500.381500.510.13
DI → INR1500.381504.243.85 *
Note: a The unconstrained model was estimated with path coefficients allowed to vary across the cross-group datasets (Eastern vs. Western). b Partially constrained means that only the target path coefficients were set to be equal for cross-group datasets. c χ2 difference between the unconstrained models and partially constrained models. * The significant difference (at p < 0.05) indicates a difference in path coefficient across three years. EXC = excitement; SIN = Sincerity; COM = Comfort; ACT = Activeness; DI = Destination image; INR = Intention to Recommend.
Table 7. Multiple Group Path Analysis: Comparison of Path Coefficients (n = 316).
Table 7. Multiple Group Path Analysis: Comparison of Path Coefficients (n = 316).
Western (n = 188)Asian (n = 128)
Pathsβt Valueβt ValueWestern vs. Asian
EXC → DI0.3903.23 *0.5096.92 *W < A
SIN → DI0.0900.710.0700.38W > A
COM → DI0.6407.44 *0.3463.08 *W > A
ACT → DI0.0620.600.0480.43W > A
DI → INR0.8009.17 *0.8588.61 *W > A
Note: Fit indices: χ2 = 1480.89, df = 434, χ2/df = 3.41, CFI = 0.911. RMSEA = 0.058; * p < 0.05; EXC = excitement; SIN = Sincerity; COM = Comfort; ACT = Activeness; DI = Destination image; INR = Intention to Recommend.

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MDPI and ACS Style

Kim, W.; Malek, K.; Kim, N.; Kim, S.“. Destination Personality, Destination Image, and Intent to Recommend: The Role of Gender, Age, Cultural Background, and Prior Experiences. Sustainability 2018, 10, 87. https://doi.org/10.3390/su10010087

AMA Style

Kim W, Malek K, Kim N, Kim S“. Destination Personality, Destination Image, and Intent to Recommend: The Role of Gender, Age, Cultural Background, and Prior Experiences. Sustainability. 2018; 10(1):87. https://doi.org/10.3390/su10010087

Chicago/Turabian Style

Kim, WooHyuk, Kristin Malek, NamJo Kim, and SeungHyun “James” Kim. 2018. "Destination Personality, Destination Image, and Intent to Recommend: The Role of Gender, Age, Cultural Background, and Prior Experiences" Sustainability 10, no. 1: 87. https://doi.org/10.3390/su10010087

APA Style

Kim, W., Malek, K., Kim, N., & Kim, S. “. (2018). Destination Personality, Destination Image, and Intent to Recommend: The Role of Gender, Age, Cultural Background, and Prior Experiences. Sustainability, 10(1), 87. https://doi.org/10.3390/su10010087

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