Localizing Cultural Values on Tourism Destination Websites

Abstract

The present study contributes to the current localization literature by revealing the effects of localizing cultural values on tourism destination websites on users’ destination image and willingness to travel. Reporting on two tests, the first is an analysis of the depiction of cultural values on 48 New Zealand, 36 Indian, and 46 Chinese destination sites. Results indicate significant differences in the cultural values exposed among the three countries. The second study reports on an experiment requiring 400 New Zealand participants to visit four versions of a fictitious experimental destination website. Commensurate with motivations for holiday tourism, results indicate that the depiction of incongruent cultural values to a target audience on destination websites generates a more positive destination image and greater willingness to travel, contradicting the current localization literature. Finally, managerial implications are also discussed.

Keywords

destination websites website localization website design cultural values

Introduction

Website localization refers to the customization of a website’s design and content in order to address cultural needs and specificities of target markets (Stamey and Speights 1999). Singh, Toy, and Wright (2009) defined website localization as “the process of customizing a website for a specific cultural group so that it seems natural or ‘local’ to members of that particular culture” (p. 282). Initially, this process was limited to language translation and the adaptation of simple website elements such as time, date, and currency. However, website localization has been extended to include adjustments to accessibility, audio, cultural values, functionality, graphics, information architecture, layout, search engines, symbols, video, and navigation among other features (Russo and Boor 1993; Stamey and Speights 1999; Collins 2002; De Troyer and Casteleyn 2004). Overall localization represents a process that requires a deep understanding of both the culture and the market in which the site will be localized (De Troyer and Casteleyn 2004; Al-Badi and Naqvi 2009) and has yet to become common practice among companies (Singh and Boughton 2005; Tixier 2005; Ajanee 2008).

This article seeks to address the following objective: to investigate the effects of localizing cultural values on tourism destination websites on users’ destination image and willingness to travel.

In order to address the objective, this article presents two studies. First is the investigation of the depiction of cultural values on tourism destination websites using the cultural framework developed by Singh, Zhao, and Hu (2003). Adaptations to the framework are suggested to address the unique features of tourism destination sites. The second study represents an experiment to investigate the effects of the localization on users’ destination image and their willingness to travel as, contrary to Singh’s framework for functional brands, in tourism we expect the incongruence between destination and target-audience values to create an increase rather than a decrease in perceived attractiveness.

In this article, the concept of culture is discussed first, followed by the localization of cultural values on websites. Afterwards, study 1 and 2 are presented. Conclusions, managerial implications, and insights for future studies are provided in the end.

Contextualization

Culture, Cultural Values, and Cultural Models

Culture as a concept has one of the highest number of definitions in the social sciences (Wallerstein 1990). In 1952, Kroeber and Kluckhohn presented a critical review of 162 definitions of culture (Kroeber and Kluckhohn 1952), and the list has increased considerably since then. For this article, culture is defined as specific collective ways of thinking, behaving and feeling, which characterize individuals of one group and distinguish them from individuals of other groups (Kluckhohn 1950; Hall 1976; Wallerstein 1990; Schwartz 1999; Trompenaars and Hampden-Turner 1998; Hofstede and Hofstede 2005).

Cultural values are the deepest and most relevant aspect of a cultural manifestation, albeit intangible. They characterize “broad tendencies to prefer certain states of affairs over others” when dealing with feelings such as evil versus good, dangerous versus safe, and moral versus immoral and are learned in the initial stages of life (Hofstede and Hofstede 2005). Values can also be described as “desirable transsituational goals, varying in importance, that serve as guiding principles in the life of a person or other social entity” (Schwartz 1994, p. 21).

Cross-cultural research at the national level is predominantly conducted through universal, value-based cultural models (Newman and Nollen 1996; ). Cultural models capture dimensions of universal human values, which manifest themselves in different magnitudes and directions across countries, and thus allow for the development of cross-cultural studies (Morden 1999). Such models provide the base for explaining systematic variation of attitudes and behaviors among different countries.Cultural models address universal values related to power, influence, hierarchy, and the involvement of individuals within social groups, reflecting the nature of human relationships (Kluckhohn and Strodtbeck 1961; Reisinger and Turner 2002). The models also include the perception and involvement of individuals toward nature and time and so represent value dimensions of human worldviews (Kluckhohn 1962).

Moreover, cultural models adopt a positivist approach to culture. Values are measured through structured questionnaires; the data are collected in a wide variety of countries and statistically analyzed to identify cultural dimensions, resulting from the grouping of sets of values (Watkins and Gnoth 2011). Following this, cross-cultural comparisons of each dimension are established. According to the results, classifications and numerical indices (cultural scores) are given to each country to reflect the magnitude and direction of the manifestation of each dimension (Hofstede 1980a; Schwartz and Bardi 2001).

The final cultural classifications (scores or indices) of universal value-based models represent a useful tool for cross-cultural research and have been frequently and successfully validated. Additionally, cultural models are frequently used for other purposes such as cultural customization of advertisements (Papavassiliou and Stathakopoulos 1997), products (Aryana and Boks 2010), websites (Baack and Singh 2007), and new product development (Nakata and Sivakumar 1996).

Of all the models, and despite criticism of methodology and age of data (Baskerville 2003), Hofstede’s stands out as the most widely adopted cultural model in the business literature (Minkov and Hofstede 2011). His model is composed of five dimensions formed by the factor analysis of responses to 56 questions. The model has been used, for example, to investigate the exposure of cultural values in television and print media advertising (Tansey, Hyman, and Zinkhan 1990; Albers-Miller and Gelb 1996; Cho et al. 1999) as well as tourists’ cultural values (Gnoth and Zins 2010; Reisinger and Crotts 2010). However, its application to websites represents a much more recent research agenda and is discussed next.

Cultural Values on Websites

The virtual world is not culturally neutral (Chau et al. 2002; Singh, Zhao, and Hu 2003; Singh and Matsuo 2004; Callahan 2005; Singh and Boughton 2005). The norms and values that govern cultural groups are also represented online and companies consciously and unconsciously depict them while developing websites. Different cultural groups have shown to have different preferences in terms of website design (Ahmed, Mouratidis, and Preston 2008; Petrie, Power, and Song 2009). With regard to the perceptions of users toward online content, respondents from distinct cultures have shown divergent responses to website quality (Tsikriktsis 2002), e-loyalty, satisfaction, and trust (Cyr and Bonanni 2005; Cyr et al. 2005; Cyr 2008) as well as in their general attitude toward a site (Singh et al. 2006a, 2006b). Therefore, a homogenized communication strategy on a website will not suit the needs and preferences of its audiences. Consequently, website localization became a topic of great relevance for academia, although not common practice within companies (Tixier 2005; Singh, Toy, and Wright 2009).

The investigation of cultural values on websites has been frequently and successfully conducted through the framework developed by Singh, Zhao, and Hu (2003). It contains the dimensions of collectivism and individualism, power distance and uncertainty avoidance (Hofstede 1980a), and high–low context dimension (Hall 1976). Hofstede’s (1980a) dimension of masculinity–femininity was excluded during a refinement of the framework because of low reliability (Singh, Kumar, and Baack 2005) and the dimension of long–short orientation was never included. Overall, the four cultural dimensions of the web-related framework are operationalized through 23 cultural categories.

The validity of the framework in the context of company websites has been verified and successfully applied in the investigation of a broad range of company sites (e.g., automotive, electronics, and retail) in a number of culturally diverse countries: United States, Japan, Brazil, Hong Kong, Russia, Turkey, Taiwan, Spain, Mexico, Germany, France, China, and India among others (Singh, Zhao, and Hu 2003; Singh and Matsuo 2004; Singh, Zhao, and Hu 2005; Singh, Fassot et al. 2006a; Singh, Fassot et al. 2006b; Baack and Singh 2007; Chang 2011; Yalcin et al. 2011).

The use of Singh, Zhao, and Hu’s (2003) framework, however, has been limited to the context of company websites, and has yet to be applied to sites that target and trigger hedonic motivations in users such as tourism destinations. While previous work in e-tourism research has referred to differences in cultural values, it targets predominantly utilitarian motivations relevant to customer relationship management issues (Sigala 2006) or other, functional aspects that relate to e-service quality (Sigala and Sakellaridis 2004). The focus on hedonic variables in an investigation of how the cultural values on sites marketing destinations are applied broadens and extends the external validity of research dealing with cultural variability in preferences. Study 1 aims to fill this gap and is presented next.

Study 1

Study 1 addresses three main objectives: (1) to investigate the depiction of cultural values on tourism destination websites, (2) to determine whether the type of destination moderates the cultural values that are exposed on tourism destination sites, and (3) to propose, if appropriate, adaptations to the cultural framework developed by Singh, Zhao, and Hu (2003) for tourism destination sites. The hypotheses of the study are presented next.

Hypotheses

This study investigates the portrayal of cultural values on official destination websites of three countries: New Zealand, China, and India. New Zealand was selected as it represents a popular destination that is geographically distant from the main markets of the United States and Europe, thus placing even greater importance on its web communication. According to Hofstede’s cultural scores (1980a), New Zealand is characterized by two extremes: it is highly individualistic and very low in power distance. Also, on Hall’s (1976) context dimension, the country is classified as being a low context culture (Morse 2003). India and China were included as their cultural scores are opposite to those of New Zealand, thereby representing an interesting contrast for a comparative analysis. India and China are characterized as highly collectivist and score high in power distance values. Also, these two countries are classified as being high context cultures (Hall, Jong, and Steehouder 2004; Würtz 2005).

Collectivism and Individualism

Collectivism (COL) and individualism (IND) refer to relationships and integration among individuals of a cultural group. In individualist societies, members are expected to emphasize their own interests before considering the community (Cho et al. 1999). As a consequence, the ties between individuals are looser. In collectivist societies, the sense of group generally comes before personal interests and so the relationships between individuals are tighter (Triandis 1995). Australia, Canada, and the United States are examples of individualist countries while Ecuador, Panama, and Colombia are ranked as collectivistic (Hofstede 1980a, 1984). New Zealand is characterized as highly individualistic (cultural score of 79), while China and India score very low on this dimension (15 and 48, respectively). Moreover, previous research has shown that Chinese and Indian company websites portray higher levels of COL in comparison to IND values (Singh, Zhao, and Hu 2003, 2005; Chang 2011). Consequently, it is hypothesized that

Hypothesis 1: New Zealand’s official tourism destination sites depict fewer Collectivist values compared to Indian and Chinese official tourism destination sites;

Hypothesis 2: New Zealand’s official tourism destination sites depict more Individualist values compared to Indian and Chinese official tourism destination sites.

Power Distance

Power distance (PD) refers to the way people accept and deal with inequalities in a society and manifests itself in both the least and the most powerful people in a cultural group (Minkov and Hofstede 2011). In countries with high PD, the unequal distribution of power among classes is clear and accepted. In low-PD countries, these inequalities are blurred and there is a social tendency for equalization of power distribution (Tsikriktsis 2002). Examples of low-PD countries are Austria, Israel, and Denmark, while Malaysia, Guatemala, and Mexico are examples of high-PD countries (Hofstede 1980a, 1984). New Zealand’s score for PD is 22, while China scores 80 and India 77. Finally, both Chinese and Indian company websites have been shown to portray high levels of PD (Singh, Zhao, and Hu 2003, 2005). As a result, it is hypothesized that

Hypothesis 3: New Zealand’s official tourism destination sites depict fewer Power Distance values compared to Indian and Chinese official tourism destination sites.

Uncertainty Avoidance

Uncertainty avoidance (UA) refers to the way people in a society deal with situations that involve uncertainty and ambiguity, or structured versus unstructured circumstances. This relation is reflected in the society’s order and structure and the way its population deals with risk-taking situations (Money and Crotts 2003). A high UA value means a population is anxious about the unknown and dislikes and avoids uncertainty. Greece, Portugal, and Uruguay are examples of countries with high UA and Singapore, Jamaica, and Denmark are examples of low-UA countries (Hofstede 1980a, 1984, 1993). Since New Zealand (49), China (40), and India (40) have very close UA scores and previous research has not found significant differences between China and India in the level of UA exposed in websites (Singh, Fassott et al. 2006), it is hypothesized that

Hypothesis 4: New Zealand, China, and India do not differ significantly in terms of Uncertainty Avoidance values on their official tourism destination websites.

High and Low Context

This dimension refers to the relation of context and codes of communication, classifying cultures as high versus low context. High-context cultures are expected to communicate in an indirect way. Meanings of messages are unclear and also subtly implied in gestures and expressions (Würtz 2005). Low-context cultures, on the other hand, are characterized by having a direct, straightforward form of communication. Meanings and objectives of messages are clearly delivered and well explained (Hall 1976). China, Japan, and Korea are examples of high-context cultures, while New Zealand, Germany, and Canada are examples of low-context countries. Consequently, it is hypothesized that:

Hypothesis 5: New Zealand’s official tourism destination sites depict more signs of Low-Context communication values compared to Indian and Chinese official tourism destination sites;

Hypothesis 6: New Zealand’s official tourism destination sites depict fewer signs of High-Context communication values compared to Indian and Chinese official tourism destination sites.

Type of Destination

The second objective of this study was to determine whether the destination type is a moderating factor in the depiction of cultural values on tourism destination sites. The aim was to investigate whether the characteristics of a destination type and the behaviors that are practiced in different markets are related to the values that are shown on the websites. For example, beach destinations, which are usually portrayed through collectivist stimuli such as groups of friends and family themes, could possibly show more collectivist values than mountain and nature destinations, which are usually associated with individualist values of solitude, isolation, and self-reliance.

The concept of culture defended by Trompenaars and Hampden-Turner (1998) and Hofstede and Hofstede (2005) suggests that cultural values are the core of a culture. The authors argue that the elements of a culture that can be seen and practiced are much more likely to change, when compared to values, as new practices constantly arise and are adopted. Values, on the other hand, are internalized by individuals during their early years and are transmitted through generations. Thus, they are much more resistant to change over time (Hofstede and Hofstede 2005). Therefore, it is hypothesized that

Hypothesis 7: The type of destination does not moderate the cultural values that are exposed on the official tourism destination websites.

Methodology

The investigation of the depiction of cultural values on the tourism destination sites was conducted through content analysis (Kassarjian 1977). Content analysis has often been used to investigate destination websites (Singh and Matsuo 2004; Singh and Boughton 2005; Choi, Lehto, and Morrison 2007; Tang et al. 2009). To evaluate the depiction of cultural values on the destination sites, the cultural framework for websites proposed by Singh, Zhao, and Hu (2003) was used. It includes Hofstede’s (1980b) dimensions of collectivism and individualism, power distance and uncertainty avoidance, and Hall’s (1976) dimension of high and low context. According to a recent review, this cultural framework represents the best scientific operational coding scheme to investigate cultural values on websites (Vyncke and Brengman 2010).

Cultural values were evaluated on a five-point Likert-type scale, ranging from “not depicted” to “prominently depicted,” as successfully employed in previous works (Baack and Singh 2007; Chang 2011; Gonzáles-Trejo 2010; Singh and Matsuo 2004; Singh, Fassott et al., 2006; Singh, Kumar, and Baack 2005; Singh, Zhao, and Hu 2003, 2005; Yalcin, Singh et al., 2011). The evaluation of values in the scale was assessed in light of (1) the size of the element (font size, graphic, advertisement, others), (2) frequency of use throughout the site, and (3) ease of visualization.

A pretest training run was conducted on 15 official UK destination sites, and it led to a discussion about consistency while applying the framework. Results indicated an interjudge reliability of 76%, which is considered acceptable (Kassarjian 1977). Following the UK pretest, the main research was conducted. During data collection, one coder examined the New Zealand and Indian sites while a second coder analyzed the Chinese sites.

Sample

A total of 130 official tourism destination websites (English versions) were analyzed: 48 New Zealand, 36 Indian, and 46 Chinese. Sites were classified as “Official” when this was mentioned explicitly or if the site contained references to, or acknowledgment from, local governments or tourism bodies. Each site was first classified according to the type of destination based on the main promotional focus of the site. Destinations were categorized as Urban, Beach/Coastal, Nature/Mountain, and Cultural, as reported in Table 1.

Table 1.

Description of Destination Types.

Country	Urban	Beach/Coastal	Nature/Mountain	Culture	n
New Zealand	13	21	14	0	48
India	7	5	12	12	36
China	19	3	10	14	46
Total	39	30	36	26	130

The unit of analysis consisted of the domestic version of each destination website. All web pages of each domestic version were analyzed. As shown in Table 1, New Zealand destination sites were mostly beach/coastal (21), while the majority of Indian destination sites were characterized as mainly nature/mountain (12) and culture (12), and Chinese as urban (19).

Results

To explore the differences between the countries on the various dimensions, a multivariate analysis of variance (MANOVA) was employed. First, Barlett’s test of sphericity (93.989 with df 20, p = .000) indicated a satisfactory correlation between the dependent variables, which confirmed the suitability of using the multivariate test. Following this, results from Pillai’s Trace indicated that the country had a significant effect on the cultural values exposed on the site: V = .917, F(12, 230) = 16.22, p = .000, partial η² = .458. Therefore a follow-up two-way ANOVA was conducted to check for significant differences between countries on each dimension (see Tables 2 and 3). The two-way ANOVA was followed by a Gabriel post hoc test, chosen because of the different sample sizes (Field and Hole 2003; Field 2005). Results for each dimension are now presented.

Table 2.

Means, ANOVA, and Reliability Scores of the Cultural Dimensions.

Cultural Values	Mean NZ	Mean India	Mean China	df	F	p	Cronbach’s Alpha, NZ/India/China
Collectivism	2.00	2.60	2.52	2	7.26	.001	.45/.39/.43
Individualism	3.86	3.17	3.71	2	11.70	.000	.61/.62/.49
Power distance	1.85	3.25	2.52	2	42.86	.000	.74/.82/.71
Uncertainty avoidance	3.28	3.33	2.99	2	4.48	.013	.57/.62/.55
High context	2.57	3.00	3.48	2	17.71	.000	.66/.61/.54
Low context	3.27	3.24	1.93	2	33.63	.000	.73/.73/.62

Note: ANOVA = analysis of variance; NZ = New Zealand.

Table 3.

Means and Standard Deviation of Cultural Categories.

Cultural Dimensions	Representation on Website	Mean NZ	SD NZ	Mean India	SD India	Mean China	SD China
COL	Community relations	2.45	0.94	3.05	0.92	3.15	1.01
	Clubs or chat rooms	1.54	0.98	2.33	1.21	2.58	1.22
	Newsletter	2.50	1.32	2.55	1.25	3.10	1.15
	Family theme	2.04	0.87	2.97	0.73	2.65	1.30
	Loyalty programs	1.47	0.82	2.08	0.93	1.10	0.37
IND	Independence theme	3.97	0.75	3.05	0.75	3.52	1.11
	Product uniqueness	3.97	0.66	4.13	0.72	4.19	0.74
	Personalization	3.62	0.81	2.33	0.75	3.41	1.06
PD	Company hierarchy information	1.93	0.80	3.50	1.00	3.15	0.94
	Pictures of CEOs	1.52	0.94	3.11	1.14	2.58	1.45
	Vision statement	1.33	0.88	2.52	1.25	3.10	0.97
	Proper titles	2.64	0.93	3.86	0.72	2.65	0.87
UA	Customer service	2.77	1.05	2.91	0.84	2.91	1.31
	Guided navigation	2.95	0.58	2.83	0.60	3.13	0.97
	Tradition theme	3.50	0.92	3.91	0.69	3.34	1.09
	Local stores	4.22	0.95	3.55	0.73	2.73	0.95
	Local terminology	2.95	0.50	3.44	0.73	2.84	1.28
HC	Politeness and indirectness	2.60	0.67	3.05	0.71	3.17	0.79
	Soft-sell approach	2.64	0.86	3.16	0.84	3.28	1.29
	Aesthetics	2.48	1.08	2.77	1.19	4.00	0.89
LC	Hard-sell approach	3.37	0.86	2.86	0.93	1.63	1.12
	Use of superlatives	3.35	0.93	3.36	0.86	2.58	1.35
	Rank or prestige of the company	3.08	0.87	3.50	0.81	1.58	0.80

Results indicated that New Zealand scored lower in COL, when compared to India and China (means: NZ = 2.00, India = 2.60, China = 2.52; F = 7.265; df = 2; p < .001) and the post hoc test revealed that the difference between New Zealand and the other two countries was significant (NZ and China, p < .000; NZ and India, p < .000). Therefore, hypothesis 1 was supported.

In IND, New Zealand scored higher than both India and China (means: NZ = 3.86, India = 3.17, China = 3.71; F = 11.705; df = 2; p < .000). However, Gabriel’s post hoc test indicated that New Zealand differed significantly from India (p > .000) but not from China (p > .384). Consequently, hypothesis 2 was only partially supported.

The findings revealed that for PD, New Zealand scored lower than India and China (means: NZ = 1.85, India = 3.25, China = 2.52; F = 42.865; df = 2; p < .000) and differed significantly from both countries (NZ and China, p < .000; NZ and India, p < .000). Thus, hypothesis 3 was supported.

UA was the third dimension analyzed. India scored the highest (means: NZ = 3.28, India = 3.33, China = 2.99; F = 4.482; df = 2; p < .013) and countries differed significantly. Therefore, hypothesis 4 was not supported.

Results indicated that New Zealand tourism destination sites scored higher LC values (means: NZ = 3.27, India = 3.24, China = 1.93; F = 33.635; df = 2; p < .000). New Zealand differed significantly from China (p < .000), though not from India (p > .997). As a result, hypothesis 5 was partially supported. Lastly, New Zealand reported fewer HC values (means: NZ = 2.57, India = 3, China = 3.48; F = 17.716; df = 2; p < .000) and differed significantly in this dimension from India (p < .009) and China (p < .000), thus supporting hypothesis 6.

Finally, results from the MANOVA also addressed the second objective of the study, as stated in hypothesis 7. The hypothesis tested whether the type of destination is a moderating factor in the cultural values employed on the sites. Hypothesis 7 predicted that the type of destination does not moderate the cultural values that are exposed on the official tourism destination websites.

The results revealed no significant difference for the influence of the type of destination on the cultural values represented on the sites (p > .05). Thus, hypothesis 7 was supported.

Adaptations to the framework

The use of Singh, Zhao, and Hu’s (2003) cultural framework to evaluate the depiction of cultural values on destination websites presented limitations. The framework was developed for company websites and lacks features that are required for, or characterize, destination websites. Based on our findings from study 1, adaptations are suggested. Changes in the framework appropriate in the context of destination sites include adaptations to the titles of cultural categories and their operationalization.

All changes to the original framework are highlighted in italics in Table 4. They are expected to contribute to future studies by enhancing its validity in the context of destination sites. The only new cultural category that is proposed is titled “Visualization of the Place” and refers to the dimension of uncertainty avoidance. During the investigation, elements such as maps of the destination, reference to the geographical location, virtual tours, live webcams, and weather charts were identified. These features enable tourists to visualize the destination and have a more accurate image of the place prior to their trip. This helps reduce anxieties and uncertainties about the place, influenced by the geographical distance and lack of information (Maser and Weiermair 1998; Lepp and Gibson 2003; Floyd et al. 2004). Finally, the adaptations were necessary to enable a more precise manipulation of cultural values during the development of the fictitious destination’s experimental website for the main study.

Table 4.

Proposed Adaptation of the Cultural Framework for the Evaluation Of Cultural Values on Tourism Destination Websites.

Cultural Dimension	Cultural Categories	Operationalization
Collectivism	Community relations	Presence or absence of sustainable tourism activities, activities relating to involvement with the local community; an emphasis on social responsibility
	Clubs or chat rooms	Presence or absence of member’s clubs, chat with destination agents, chat with interest groups, message boards, discussion groups and live talks, social network sites
	Family theme	Pictures of families, pictures of teams of employees, groups of tourists, emphasis on team and group activities and tourists as a family
	Newsletter	Online subscriptions, magazines, and newsletters
Individualism	Independence theme	Images and themes depicting self-reliance, self-cognition, achievement, isolation and self-fulfillment
	Uniqueness of the destination	Emphasis on the unique features and differentiating aspects of the destination
	Personalization	Features such as attractions recommendations, individual acknowledgements or greetings from the destination, travel planners, web page personalization, and customized travel packages
Power Distance	Destination hierarchy info	Information about destination managers, politicians, local government or administration and hierarchy of the tourism sectors
	Pictures of celebrities	Pictures of important people in the society, including politicians, athletes, artists, and other celebrities
	Proper titles	Titles of the important people related to the destination and titles of the people in the contact information
	Vision statement	Statement about the destination from destination managers or people who represent power in the society
Uncertainty Avoidance	Customer service	FAQs, tourist service, tourist contact, tourist service e-mails and toll-free numbers available 24 hours
	Guided navigation	Site maps, well-displayed links, links in the form of pictures or buttons, forward, backward, up, and down navigation buttons
	Tradition theme	Emphasis on history, emphasis on respect, veneration of elderly and the culture, and phrases like “most respected destination,” “keeping the tradition alive,” “for generations,” etc.
	Local services	Contact information for local tourism-related companies such as hotels, travel agencies, restaurants, and others; also contact information for personal safety services, such as police and hospitals
	Visualization of the place	Maps of the destination and reference to geographical localization, virtual tours, live webcams, weather charts, etc.
	Local terminology	Use of country-specific metaphors, names of festivals, puns, a general local touch in the vocabulary of the web page
High Context	Aesthetics	Attention to aesthetic details, liberal use of colors, high bold colors, emphasis on images and context, and use of love and harmony appeal
	Politeness and indirectness	Greetings from the destination, images and pictures reflecting politeness, flowery language, and use on indirect expressions like “perhaps,” “probably,” and “somewhat”; overall humbleness in the destination philosophy and information
	Soft sell approach	Use of affective and subjective impression of intangible aspects of a product or service and more entertainment theme to promote the destination
Low Context	Hard sell	Discounts, promotions, coupons, and emphasis on products and services advantages using explicit comparison
	Rank or prestige of the destination	Features like destination’s rank in the country, listings, and numbers showing the growth and importance of the destination
	Use of superlatives	Use of superlative words and sentences: like “we are the number one,” “the most visited destination,” the leader,” and “world’s most famous”

Note: Adaptations to the original framework are highlighted in italics.

Limitations

First, the classification of destinations according to the main focus of the site or main experiences fostered may represent a limitation. Destinations are complex products that can encompass a wide range of experiences. Second, having only one coder coding each site also represented a limitation. The inclusion of multiple coders would have enhanced the reliability of findings and allowed the verification of the interjudge reliability measured for the main study. Also, the level of site development and sophistication may influence the website elements exposed and, as such, the values that are represented. Thus, future studies involving cultural values online must consider this as a possible moderating factor for the depiction of values on such sites. Finally, the investigation of only English versions of sites may represent a limitation to the study, as different language versions of the sites may well be localized to target markets or present unintentional differences. As such, future studies should investigate differences in the depiction of cultural values in different language versions of the same destination website.

Study 2

Study 2 presents an experiment conducted to investigate the influence of the localization of cultural values on tourism destination websites on users’ destination image and their willingness to travel. The hypotheses that guided study 2 are described next.

Hypotheses

The success of cultural congruity between websites and users in previous studies (Baack and Singh 2007; Vyncke and Brengman 2010) suggest that it can be generalized to every industry context. For this reason, the hypotheses of this study focus on a context that involves situational perceptions and hedonic motivations. More importantly, tourism destination websites have not been investigated in previous cultural localization studies.

The effects of cultural congruity in the context of tourism destination sites are still unknown. However, to investigate the effectiveness of a marketing action in the tourism context, it is essential to understand tourist motivations (Fodness 1994). Our understanding of tourists’ motivations suggests that cultural congruity may not be a successful web strategy, especially when it comes to leisure travel.

The development of an individual’s motivations and attitudes toward traveling is an inner process influenced by the values they possess. Tourism is a pleasure-seeking activity and many travelers are driven to satisfy their desired self rather than the social norms of the culture they belong to (Gnoth 1997). The motivation to travel is associated with an attempt to escape from the social norms or regulations that rule the culture that one lives in (McIntosh and Goeldner 1990; Gnoth 1997; Kim and Lee 2000). Therefore, tourism is a context in which an individual’s behaviors and perceptions are often related to their ideal self (how individuals would like to perceive themselves) and situational self (self-image tailored for specific situations) (Todd 2001). This condition may be reflected in behaviors that would be considered unexpected in a tourist’s cultural group or daily social environment (Cohen 1974).

Kim and Lee (2000) argue that tourist motivations are culturally driven, and that individualist and collectivist values are determinants of the motivation to escape from the social norms in which one is embedded. In individualist cultures, people have less regard for rules and norms, and impulse behavior is more usual when compared with collectivist cultures (Triandis 1988).

The need for escape from social norms is associated with values related to exploration, prestige, evaluation of the self, and social interaction (Dann 1981). It represents such a universal motivation for leisure traveling that in some instances it is considered to be a culturally learned stereotype (Mannell and Iso-Ahola 1987). In fact, Cohen (1972) posits that novelty-seeking and escapism are the basic and most primitive motivations for tourism. The continuum of novelty and familiarity is an underlying variable that defines social typologies of tourists (Cohen 1972).

Furthermore, tourism represents a form of hedonic experience where feelings, emotions, and fantasies are fostered by the destinations to stimulate behaviors (Holbrook and Hirschman 1982; Pike and Ryan 2004; Hosany and Gilbert 2010; Kim, Ritchie, and McCormick 2012). Tourists’ recognition of their need for experience represents an initial factor in traveling, which then ignites the tourist’s search for signs in objects, situations, and events to satisfy their desire (Hunt 1975; Roehl and Fesenmaier 1992; Gnoth 1997). When tourists recognize the need to travel, they engage in trying to identify destinations that are associated with their travel motivations (Lam and Hsu 2006). When tourists perceive an association between a destination and their motivations and desired self-image, it enhances the intention to travel to the destination and their expected satisfaction with the trip (Murphy, Benckendorff, and Moscardo 2007; Tasci and Gartner 2007).

More recently, the internet has become a major platform to promote destinations, through the use of stimulating visuals that enhance a user’s travel intentions (Fürsich and Robins 2002; 2004; Kaplanidou and Vogt 2006). Consequently, tourism destination websites have become one of the main information sources for users to identify destinations that relate to their needs, motivation, and self-image (Frías, Rodríguez, and Castañeda 2008).

The design of a destination site is critical in providing a look and feel of the place online (Govers and Go 2005, Govers, Go and Kumar 2007a; 2007b). Thus, the site’s design has a great impact on the symbolic image that individuals develop of the destination (Mohammed 2004; Lepp, Gibson, and Lane 2011). When cultural markers and cultural values are localized, the site is purposely tailored to become culturally congruent with its target market.

A culturally congruent site portrays a design and values that are expected to be perceived as familiar to the culture it is tailored to (Barber and Badre 1998; Sun 2001). The familiarity of the user with the site facilitates the interpretation of messages and the navigability on the site. Consequently, it leads to positive attitudes toward the site and enhances behavioral intentions, such as purchase intention (Singh, Furrer, and Ostinelli 2004; Singh, Fassott et al. 2006; Baack and Singh 2007).

However, with reference to Cohen’s (1972) spectrum of novelty and familiarity, cultural congruity enhances the familiarity of the user with the destination. Alternatively, cultural congruity reduces novelty elements of the destination and the site, while cultural incongruity between users and sites is expected to enhance elements of novelty.

In the context of leisure tourism, cultural incongruity is then expected to generate more positive perceptions when compared to cultural congruity, as situational factors determine one’s perceptions (Cohen 1974; Todd 2001). Thus, in this context, high cultural congruity could lead to tedium or boredom related to the place (Luna, Peracchio, and Juan 2002), thereby leading to less positive perceptions.

As a result, in the context of leisure tourism, culturally localized websites are expected to negatively impact the user’s perception of the attractiveness of the place and its website because of the reduction of novelty signs. Accordingly, culturally localized websites may generate lower intention to travel and less positive destination image when compared to websites of the same destination that are culturally incongruent.

In summary, a user’s motivation and self-image, related to the product type portrayed in the sites, are expected to have a direct influence on the effectiveness of the cultural localization of websites. As a result, in the leisure tourism context, tourists are more likely to appreciate and be attracted by cultural incongruity toward destination websites, rather than cultural congruity. Therefore tourism destinations may generate more positive perceptions in prospective visitors by reducing the user’s familiarity with the site and emphasizing novelty features with regard to the target culture. To test this, the following hypotheses are proposed:

Hypothesis 1: Destination websites that portray congruent cultural values of a target market generate a less positive destination image in users when compared to destination websites that portray incongruent cultural values.

Hypothesis 2: Destination websites that portray congruent cultural values of a target market generate lower willingness to travel in users when compared to destination websites that portray incongruent cultural values.

Experimental Design

The research consisted of an experiment with a 2 × 2 between-groups design. For the experiment, four versions of a fictitious tourism destination website tailored for New Zealanders were created: two versions depicting congruent cultural values of New Zealanders (the versions differed in the design of the site) and two versions with incongruent cultural values (again the versions differed in the design of the site). The manipulations of cultural values were conducted based on the suggested adaptations of Singh, Kumar, and Baack (2005) cultural framework for tourism destination websites (Table 4), presented in study 1, and aligned with Hofstede’s cultural scores (1980) for New Zealand:

Congruent values: The New Zealand culture is characterized by two extremes: highly individualistic and very low power distance (Hofstede 1980a). Also, based on Hall’s (1976) context dimension, the country is classified as a low context culture (Morse 2003). Congruent values were portrayed in the first and fourth conditions of the experiment.

Incongruent values: The incongruent cultural values were manipulated in order to reflect values that do not characterize New Zealand culture, according to Hofstede’s cultural scores (1980a) and Hall’s (1976) classification. Thus, incongruent versions emphasized collectivist values, high power distance values, and high context values. Incongruent values were depicted in the second and third conditions of the experiment.

A manipulation check was conducted with 20 postgraduate students of the University of Otago (New Zealand) to verify the manipulation of congruent and incongruent cultural values. Participants were given definitions of the constructs related to the investigation and assisted during the evaluations to ensure their understanding. Each student evaluated one of the four versions of the experimental website, to identify cultural values and cultural markers exposed on the site. The students who participated in this analysis did not participate in the main study. Respondents answered the adapted scales of Singh, Zhao, and Hu’s (2003) cultural framework, proposed in the first preliminary research (Table 4). The scale items for each cultural dimension were answered using a five-point Likert-type scale ranging from “not depicted” to “prominently depicted.”

A dependent t-test was conducted for the analysis. Results indicated significant differences (p < .05) in the cultural values exposed for all dimensions.

Development of Experimental Website

The content of the site (photos, texts, and headings) was evaluated by four postgraduate researchers in the areas of culture, tourism, and psychology. The content was ranked according to the cultural dimensions that were used on the manipulations (collectivist–individualist, high–low power distance, and high–low context). Only material that achieved consensus among all judges was used in the different versions of the site.

Each version of the experimental website contained an average of 26 web pages, covering information about the destination, a detailed map of the place, a list and description of eleven different types of attractions, a description and list of accommodation, events, a detailed list of restaurants and bars, local cuisine, testimonial page, contacts, shopping, and a photo gallery.

Experimental Procedures

Participants navigated the site and chose their top two places to eat, sleep, and for activities to do. Following this, they answered an online survey that included, among other variables, the evaluation of destination image (Baloglu and McCleary 1999) and the participant’s willingness to travel to the destination (Krishnamurthy and Sujan 1999). The destination image scale proposed by Baloglu and McCleary (1999) is composed by 14 functional attributes (measured in a 5-point scale) and 4 affective and 1 overall attribute (measured on a 7-point scale). Willingness to travel was evaluated on a 1- to 5-point Likert-type scale, ranging from “totally disagree” to “totally agree.” Finally, online trust was measured as a possible covariate, through the adaptation of the scale of Cyr et al. (2005). Participants took an average time of 20 minutes to complete all tasks.

Before data collection, a pretest of the experiment was conducted with 30 New Zealand undergraduate students, and necessary changes were made to the site and survey. After this, the experiment was conducted with 400 New Zealand undergraduate students from the University of Otago, 100 per condition.

Results

Convergent and Discriminant Validity

First, a principal components factor analysis with Varimax rotation was conducted for data summarization and to test for dimensionality of all scales. Data summarization was necessary as the destination image contained 18 items and the constructs suggested the existence of more than one dimension. Moreover, previous studies adopting multiitem scales for destination image indicated more than one dimension (cognitive and affective image) through exploratory factor analysis (San Martín and Rodríguez del Bosque 2008).

The factor analysis reduced the number of destination image scale items from 18 to 8. Ten items with poor loadings (<.3) were removed during the analysis, as suggested by Hair, Black et al. (2006). As predicted, the analysis suggested two destination image factors: infrastructure for tourism (cognitive image) and affective image.

Second, the Kaiser–Meyer–Olkin (KMO) measure verified the sampling adequacy for the analysis (KMO = .848). Moreover, Barlett’s test of sphericity, χ²(820) = 8099.044, p = .000, indicated that correlations between items were sufficiently large for the analysis. Results of the factors accounted for 69.0% of the total variance of the data. Factors presented eigenvalues over Kaiser’s criterion of 1, and factor loadings over .3, which is acceptable, in view of the large sample size (Field 2005; Hair, Black et al. 2006). Thus, convergent validity was accounted for. Discriminant validity was verified through a correlation matrix of the factors.

Destination Image and Willingness to Travel

Barlett’s test of sphericity (240.601 with df 9, p = .000) indicated satisfactory correlation between the dependent variables, which revealed the suitability of using the multivariate test. Second, Levene’s test revealed that the assumption of homogeneity of variance was not violated (p > .05), except for the factor of “infrastructure for tourism” (p < .05). Following this, a four-way multivariate analysis of covariance was used to identify possible significant differences among the four conditions in relation to dependent variables regarding destination image and willingness to travel. The means and standard deviations for each evaluation category are shown in Table 5.

Table 5.

Means and Standard Deviations for the Destination Image and Willingness to Travel.

Factors	Scale Items	Conditions
Factors	Scale Items	1st	2nd	3rd	4th
Infrastructure for tourism	Standard hygiene	3.87/.74	3.89/.73	3.84/.69	3.82/.74
	Personal safety	3.58/.68	3.62/.67	3.61/.68	3.45/.82
	Quality of infrastructure	3.59/.73	3.64/.67	3.69/.74	3.66/.74
	Unpolluted environment	4.12/.72	3.97/.70	3.99/.74	3.98/.77
	Good nightlife	3.88/.76	3.79/.71	3.84/.74	3.78/.74
Affective image	Sleepy–arousing	4.93/1.2	5.05/.1.0	5.3/.1.0	5.01/1.1
	Boring–exciting	5.30/.89	5.87/.79	6.08/.84	5.69/1.1
	Friendly/hospitable people	3.87/.83	4.06/.73	4.03/.74	3.83/.82
Overall image	Overall image	5.60/.82	5.87/.83	6.27/.73	6.05/.91
Willingness to travel	After navigating on their website, I want to visit Bomanjo	3.23/.77	3.42/.79	3.78/.85	3.59/.82
	I am interested in visiting Bomanjo	3.79/.65	3.97/.65	4.24/.69	4.12/.65
	I would recommend others to go to Bomanjo	3.39/.68	3.56/.68	3.83/.72	3.71/.82

Results from Pillai’s Trace indicated that there was a significant effect of the manipulation of cultural values, V = .049, F(4, 389) = 5.05, p = .001, after controlling for the effect of trust, V = .057, F(4, 389) = 5.85, p = .000. A follow-up four-way independent analysis of covariance revealed significant effect of cultural values on affective image F(1, 392) = 9.26, p = .002, partial η² = .023; overall image F(1, 392) = 7.85, p = .005, partial η² = .020; and willingness to travel F(1, 392) = 8.26, p = .004, partial η² = .021.

The findings suggest that the perception of cognitive attributes of the destination image is not influenced by cultural values exposed on destination websites. Instead, the affective and overall image, which represent holistic evaluations of the place, are influenced. Moreover, the cultural values portrayed in destination websites also influence the user’s willingness to travel to the destination. All results are shown in Table 6, and significant values are highlighted in bold. The results indicate moderate to low effect sizes for all three significant factors (η² = .02; Field and Hole 2003).

Table 6.

ANCOVA Results for Effect of Cultural Values on Destination Image and Willingness to Travel.

Dependent variables	F	p	η²
Infrastructure for tourism	.885	.347	.002
Affective image	9.26	.002	.023
Overall image	7.85	.005	.020
Willingness to travel	8.26	.004	.021

Note: ANCOVA = analysis of covariance.

As incongruent cultural values led to more positive affective and overall images, hypothesis 1 was partially supported. Finally, the finding that congruent cultural values led to a lower willingness when compared to incongruent cultural values supports hypothesis 2.

Discussion and Conclusions

To date, studies involving cultural localization of websites have indicated that the process leads to positive perceptions on the part of users toward the sites and enhances behavioral intentions, such as purchase intention (Baack and Singh 2007). The studies also revealed that users tend to prefer culturally localized websites rather than nonlocalized websites (Chau et al. 2002; Singh, Furrer, and Ostinelli 2004; Singh, Fassott et al. 2006).

Thus, the most striking finding of this study is the apparent inefficiency of cultural congruity to achieve more favorable perceptions. The results indicate that in the context of leisure tourism and hedonic, exploratory browsing, information search, and decision making, website versions that portray incongruent values lead to more positive perceptions of the place and more favorable behavioral intentions of traveling to the destination. They therefore direct our attention toward an additional user situation and perspective to those in the existing literature and studies. While this does not undermine the importance of adopting a user-centric approach, rather than a product- or destination-centric approach (Sigala and Sakellaridis 2004; Sigala 2006), the findings suggest that users’ situational parameters and hedonic motivations also impact the need for congruity between user and website values. The main theoretical explanation for this finding lies with understanding users’ motivations, the user’s self-image adopted while navigating the site, and the product category. All of these factors are visually represented in Figure 1.

Figure 1.

Theoretical rationale involving self-concept, cultural congruity, and motivation.

Our findings signal the need for future research on value and site congruency. The positive outcomes of cultural congruity detected by previous research may be attributed to the fact that those studies focused on contexts in which the familiarity of the user with the site facilitated information searching (or any other task conducted in the site), and by reducing the cognitive effort required by the user to complete online tasks (Luna, Peracchio, and Juan 2002; Nantel and Glaser 2008). This was because the users’ online behavior was mainly based on utilitarian motivations (Childers et al. 2001; Martinez-Lopez et al. 2006). In these situations, we may assume that users possibly adopt the role of problem solvers (Hirschman and Holbrook 1982) in which cultural value and site congruency are in a linear relationship. However, we may now also accept that the need for congruency is not linear in all situations and possibly contains thresholds as defined by users’ levels of tolerance for novelty.

Previous studies, for example, have used websites of multinational companies (Cyr et al, 2005, 2010; Singh et al. 2004, 2006) and manufacturing companies (Baack and Singh, 2007). These examples demonstrate scenarios in which the websites are expected to trigger mostly utilitarian motivation (Martinez-Lopez et al. 2006). However, tourism destination sites represent a very divergent context when compared to company websites (Kim and Fesenmaier 2008). Tourism involves hedonic motivations in which information search and consumption are related to enjoyment, fantasy, and sensory stimulation (Crompton 1979; Hirschman and Holbrook 1982; Goossens 2000).

In contrast to utilitarian motivation, leisure tourism consumer experiences hold vague expectations prior to the trip and complex satisfactions after it (Arnould and Price 1993). For this reason, destinations have the responsibility of fostering, on and offline, the opportunity for tourists to engage in experiences (Tung and Ritchie 2011). Cultural congruity represents the opposite. It enhances the familiarity of the user with the site, thus reducing possible novelty elements. For this reason, leisure tourism represents a context in which high congruity seems inappropriate. As tourists’ familiarity with the destination increases, their information search decreases (Brucks 1985). Thus, the relevance of destination websites in the decision-making process is reduced.

Furthermore, the ineffectiveness of cultural congruity identified in this research does not contradict results from previous research. In fact, the theoretical discussion of this research supports findings found in previous studies. It emphasizes the need to discuss the effects of website localization in light of the users’ motivations, self-image (adopted when dealing with the website and the product types it portrays), and the characteristics of the industry sector. All of these issues must be addressed when discussing users’ evaluation of websites or the effectiveness of cultural localization. Thus, the theoretical rationale enables a clearer understanding of previous, current, and future localization studies.

Finally, this paper provides a practical contribution for destination website designers. The adaptation of Singh, Zhao, and Hu’s (2003) cultural framework for tourism sites (Table 4) allows future tailoring of destination sites to target audiences, according to their cultural profile and based on the cultural classifications of Hofstede (1980a) and Hall (1976).

Limitations and Future Research

The results are limited to a New Zealand context. Future cross-cultural localization studies involving destination sites are needed to provide a deeper understanding of the effects of cultural localization on tourists’ destination image and willingness to travel.

The use of student sampling has been criticized by academics and may be considered a limitation. It is therefore suggested that the research be later replicated with nonstudent subjects (Burnett and Dune 1986; Potter et al. 1993; Peterson 2001).

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research was partially funded by the Department of Marketing of the University of Otago and by Myth Branding and Digital Agency (Web design company responsible for the technical development of the experimental sites.

Author Biographies

Francisco Tigre Moura, PhD, is a Lecturer at IUBH School of Business and Management in Bad Honnef, Germany. He obtained his PhD from the University of Otago, New Zealand. He also holds a Masters in Business Administration and a Bachelor degree in Tourism Management, both from Universidade Federal de Pernambuco, Brazil. His research interests include tourism marketing online and the influence of Internet and mobile technology in society and in human experiences.

Juergen Gnoth teaches at the University of Otago in New Zealand. His interests relate to Consumer Behaviour, and particularly in research relating to Experiencing (incl. expectations and satisfaction research), Place Branding, Social Systems and Phenomenology.

Kenneth R. Deans is an Associate Professor at the University of Otago, New Zealand. His research and teaching interests include B2B clusters, strategy and Internet issues.

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