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Article

Perceived Sustainable Destination Image: Implications for Marketing Strategies in Europe

by
Arminda Almeida-Santana
1,* and
Sergio Moreno-Gil
2
1
Research Group in Business Management (Gide), University of León (ULE), 24007 León, Spain
2
Institute of Tourism and Sustainable Economic Development, Universidad Las Palmas de Gran Canaria, 35001 Las Palmas de Gran Canaria, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(22), 6466; https://doi.org/10.3390/su11226466
Received: 30 October 2019 / Revised: 11 November 2019 / Accepted: 15 November 2019 / Published: 17 November 2019
(This article belongs to the Special Issue Optimal Tourism Development)
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Abstract

There is currently a growing concern about the consequences of tourism activity on the environment. In this regards, sustainable management is understood as a key element that can help destination marketing organizations (DMOs) to improve a tourist destination’s competitiveness. This study provides some clues about the best way to develop the image and branding of a destination using the concept of sustainable image. Through an analysis of 28,947 tourists from 18 European countries, this paper studies what sociodemographic, cultural, and behavioral characteristics of tourists influence their perception of sustainable destination. The results of the binomial logit analysis show that destination primary and secondary images, motivations, cultural background of tourists, and sociodemographic characteristics are determinant factors explaining the perception of sustainable destination image (SDI). Thus, the fundamental role of segmentation to positioning a destination as a sustainable destination is suggested. The study provides interesting recommendations for DMOs in order to be able to design better marketing strategies focused on destination image.
Keywords: sustainable destination; destination image; marketing strategies; communication; segmentation sustainable destination; destination image; marketing strategies; communication; segmentation

1. Introduction

A concern of academics over the last couple of decades has been that of destination image [1], with it becoming one of the key topics among researchers. Although there have been many attempts to understand the concept of the image of a destination [1,2,3], it can be thought of as the accumulated perception of both cognitive and affective evaluations [4,5,6]. Almeida-Santana and Moreno-Gil (2018) [7] pointed out that the image’s cognitive component concerns the beliefs and information in respect to a destination’s attributes which are retained by tourists, whereas emotional feelings or responses to the characteristics of a place represent the affective component. Destination image has been defined by Bigne, Sanchez, and Sanchez (2001) [8] as the subjective interpretation of reality within the tourist’s mind.
There is no doubt that tourists’ profiles have undergone a significant change in recent years. Previous studies indicate a greater awareness of tourists on how their activity can impact on the destination’s environment, society, and culture [9]. Thus, it can be said that sustainable tourist behavior is an extant and thriving field of study [9,10]. Some authors [11,12,13] dare to indicate that more and more tourists make purchases with an eye to the environmental, social, and economic quality of products. There is a growing trend towards the consumption of sustainable brands that influences the destination choice [14,15,16,17]. Therefore, currently, destinations are more concerned with sustainability in their response to adapt to the new demands of tourists [18]. Destination marketing organizations (DMOs) must be able to convey a sustainable destination image if they want to improve their levels of competitiveness.
Notable efforts have been made within the literature to investigate factors which have an influence on image [18,19]; however, no research has undertaken analyses on the factors which determine a tourist’s perception of an image of sustainable destination (SDI). Thus, the aim of this study is to understand whether tourists’ sociodemographic, cultural, and behavioral characteristics influence their perception of a destination as being sustainable.

2. Literature Review

2.1. Sustainable Destination Image

A greatly explored construct within tourism literature is that of destination image [1,20,21]. Since its inception into the academic studies in the early 70s, scholars have sought to clearly define this concept. Fakeye and Crompton (1991) [10] defined destination image as the mental representation based on a group of images chosen by the tourist from the large amount of images available through different information sources. The concept of a subjective, personal perception of the tourists was added latter by other researchers [8,22].
Sustainable destination has been defined by past studies as a destination which provides economic development, a higher level of standard of living, ecological preservation, and social and cultural heritage preservation [23,24]. However, SDI may be differently perceived by visitors.
Destination image research attempts to conceptualize the concept of destination image and to identify its dimensions [25,26,27]. These destination image researchers endeavor to unravel the components of this concept in order to facilitate DMOs in shaping strategies regarding customer segments. Thus, Echtner and Ritchie (1991) [19] claim a need for more research that will aim to provide an improved understanding of the destination image, further conceptualizing it in terms of an accumulation of attributes. Besides the more holistic impressions, it would also be important to measure the cognitive and affective images with the consideration immersed within the characteristics of the destination and the personal perception of the tourists [20,28]. Thus, the primary image is formed via acquisition of information through visitation of the destination [20], while information sources that are organic, induced, and autonomous form the secondary image [29].
Past research assumes that environmental and socioeconomic aspects of a location exhibit a direct linkage to the image of the destination [30], highlighting the importance of sustainability as a destination’s positioning strategy. Consequently, Souza et al. (2014) [30] have claimed that the concepts of sustainability and image have a grounding in common basic aspects. However, past studies include sustainability as a component of cognitive image [27,31,32]. Given this prominence that sustainability is taking today, its association with the affective and general image of the destination is crucial.

2.2. Motivations

Motivations, as one of the key influences that guides the development of a destination image, are included in the models of destination choice and image formation [33]. These motivations can be grouped with respect to push and pull factors [34]. For Dann (1977) [35], what can be termed as internal (push) motives are linked to tourists’ wishes and include such aspects as desires to escape or rest and to acquire prestige, adventure, and social interaction. Pull factors, on the other hand, are connected with a destination’s attractiveness and resources. Previous research has shown that an individual’s internal motivations significantly affects the formation of destination image [20,25]. For instance, Baloglu (2000) [36] found the relationship between motivations to relax, escape, and gain knowledge to be statistically significant.
In current tourism literature, motivation has often been used as a criterion of segmentation [37,38,39] with this method being suggested as one of the most effective [34,40]. Easy categorization of heterogeneous groups of tourists via these motivational factors has been shown to be possible by numerous empirical studies [41,42,43]. Thus, an expansion of knowledge on the various motivations of tourists is important for the positioning of brands in differing markets [44,45]; however, previous literature has not paid special attention to the relationship between motivations to travel and SDI. Thus, the contribution of this study resides in a better understanding of this relationship. This can help DMOs in their choice of content to be communicated according to the motivations of tourists.

2.3. Cultural Background

A considerable volume of research has utilized national culture as a rationale for market segmentation [45,46,47], and thus, it is felt to be an appropriate basis for segmentation. Nationality has received growing attention in research studies since Hofstede (1980) [48], as it has been argued to be one of the most influential aspects that affects tourism behavior [49,50,51,52] and influences destination image [53,54,55,56,57]. Furthermore, national culture plays a key role in the way tourists from different countries interpret the sustainability and, in consequence, as a fundamental element on the sustainability image of tourism destinations [30].
Nevertheless, extant research on the manner in which national culture affects consumer behavior [58] and specially perceived destination image [59] is still not sufficiently conclusive. Researchers are seeking further studies on segmentation which utilize geographical criteria [60,61] that better guide the development of more improved, efficient marketing strategies [45,62].
Considering that which has been mentioned so far, the purpose of this paper is to initiate debate on the relationship between the image of tourism destination sustainability and the tourists’ countries of origin. There is importance, both with respect to the academic realm and for practitioners, to have clarity in understanding how the national culture of tourists might cause SDI to differ. Through this, the design of better marketing strategies will be possible, which will lead to a more appropriate positioning of sustainable tourism destinations within different cultures.

2.4. Sociodemographic Characteristics

Consumer behavior research has traditionally been linked to sociodemographic characteristics, and these have been frequently used as segmentation criteria [63]. The incorporation of sociodemographic variables as factors influencing the perception of a destination’s image has occurred in most image formation models [31,64]. Studies have identified that there are differences in image perceptions by gender, age, and level of education [31,65].
Given the changes in consumer behavior in relationship with sustainability, there is a need for the development of further research on SDI from the perspective of market segmentation. It is feasible that segmentation criteria that has a basis in sociodemographic characteristics may not be fully aligned with the profile of sustainable tourists.

3. Methodology

3.1. Population

Generating greater than half of the yearly international arrivals, Europe represents the world’s largest outbound region with respect to tourist flow [66]. Therefore, tourists aged 16 or over who, within the last two years, had gone abroad and who had made use of the Internet to plan their trip were the target population for this research. Tourists from the 18 major European countries, in tourist terms, were utilized for this study: Germany, Austria, Belgium, Denmark, Spain, Russia, Finland, France, Netherlands, Ireland, Italy, Luxembourg, Norway, Poland, Portugal, United Kingdom, Czech Republic, and Sweden.

3.2. Sample Selection

This research was progressed through the use of a computer-assisted web interview (CAWI). A sample from the 18 countries was considered and was yielded from a database of panelists residing in each of these countries. It was to maintain the representativeness of the sample with respect to the population of each country. In order to achieve this, a random selection of the sample was undertaken, with this being based on the variables of stratification of the geographical area and province, on the one hand, and of the criteria of gender and age, on the other. Participation in the research by the selected sample was sought by sending them a personalized e-mail, with a personalized link being embedded in the e-mail that led them to an online survey. To achieve the expected quantity of completed surveys, two reminders were sent during the three months of fieldwork in the countries so as to encourage response. This culminated in the final sample consisting of 28,947 tourists.
Visits to the Canary Islands (Spain) was the focus of the analysis of the results, in particular with respect to the sustainable perceived image of this destination. In addition to the reason of convenience, the Canary Islands were chosen as the specific case due to it being a leading destination in Europe which enjoys a well-known brand throughout the continent. Given that it receives approximately 15 million tourists annually and has a complex economic ecosystem [7], these are factors which make it a perfect subject for consideration of the topic of sustainability. One of the 17 autonomous communities of Spain, the group of Canary Islands is formed as an archipelago located in the Atlantic Ocean.
Island destinations face specific challenges regarding tourism development [67]. The Canary Islands are highly relevant as a place of research, due to steady discussions about tourism development and growth [68] and the islands’ character as an experimental zone for sustainable tourism in the context of an overflowing capacity of tourism growth [69]. Thus, sustainability in the Canary Islands destination has been the subject of a great amount of recent studies [70,71,72,73].

3.3. Questionnaire, Quality Control, and Data Analysis

The questionnaire was translated into the languages of each of the 18 countries. The survey was undertaken once the questionnaire had been pre-tested in the languages of the potential tourists and questions that had raised difficulties in comprehension had received pertinent corrections. Upon completion of the necessary programming, the online system undertook a review of all of the conducted surveys. This included detecting the amount of time that respondents had taken to complete the survey, and any survey answered in less than 5 minutes was deemed as not valid. A binomial logit analysis was performed after completion of the fieldwork. A logit model based on the theory of random utility was chosen for this research. In utilizing this model, robustness in the estimated results is guaranteed, along with fulfilment of the properties of the conventional utility functions as established by the theory of the consumer.
With respect to the variables included in the model, tourists were invited to answer how sustainable they perceived the Canary Islands destination. A score of 1 indicates very unsustainable and 7 indicates very sustainable. For the statistical treatment of this variable, following the study of Almeida-Santana and Moreno Gil (2018) [7], it was necessary to dichotomize it, understanding that tourists who marked a 6 or 7 out of 7 were considered to perceive the destination as sustainable, while we understand that those who gave values between 1 and 4 do not perceive the Canary Islands destination as sustainable. Table 1 shows the description of all the variables included in the estimated model.

4. Results

Below, in order to fulfil the aim of this study, a binomial logit model has been estimated with the perception of a sustainable destination image (SDI) as dependent variable. The model explored the existence of a relationship between SDI and sociodemographic, cultural, and behavioral characteristics of tourists.
A factor analysis was undertaken prior to estimating the model so as to examine the motivations’ dimensions. The aim for this was to affect a reduction in their dimensions and an appropriate identification of the determining factors. With due regard to the criteria addressed in the literature, each item has been classified in respect to the higher loading. With the majority of the factor loadings being greater than 0.40, this is an indication of a good correlation between the items as well as the factor grouping to which they belong [75,76]. The validity of these analyses was further supported by the outcome of Pearson correlation coefficient calculations for each of the variables and factors.
Completion of the factor analysis on the motivations revealed four dimensions that explain 55.93% of the variance. As portrayed in Table 2, the first factor incorporates 3 items which we have labelled as “Fashion, Fun, and Friends”. Four items are collected together for the second factor, namely “Sun, Beach, Relax, and Family”. The third factor also holds 4 items, in this instance, related to “Sports and Nature”. Lastly, 2 items comprise the fourth factor named “Knowledge”. Regarding the findings of the Cronbach’s alpha calculations, it is necessary to consider that MOT4’s low value could feasibly be consequential to this factor only consisting of 2 items, given that Cronbach’s alpha is known to be sensitive to the number of items in a scale [68]. It can be said that these findings are largely in accordance with the literature [18,55,77,78].
Table 3 summarizes the results of the estimation for the proposed model. Regarding the consumer’s previous experience as a tourist in a specific destination, it was unsurprisingly found that the greater the number of times a destination is visited, the greater is the likelihood of SDI being evident (β = 0.004; p < 0.01). Furthermore, it is also not surprising that a tourist having had a recent travel to the Canary Islands increases the probability of perception of SDI (β = 0.200; p < 0.01). These findings align with the argument that primary sources of information influence the perceived destination image, as suggested by Beerli and Martín (2004) [20].
As for advertising, tourists having seen advertisements about the destination have a positive influence on SDI (β = 0.187; p < 0.05), and thus, this portrays the importance of this tool being utilized by destinations (as secondary sources of information) for enhancing the image of sustainable destination.
Furthermore, the motivations related to going to places that are fashionable, to looking for entertainment and fun, and to enjoying and spending time with friends have positive effects on SDI (β = 0.365; p < 0.01). In the light of the results of our study, those tourists are 40% more likely to perceive the destination as sustainable. The motivations of rest and relaxation, of spending time in a destination with good beaches and pleasant climate, of enjoying and spending time with family, and going to comfortable places all positively influence SDI (β = 0.244; p < 0.01). They are 27.7% more likely to perceive SDI. The motivations of doing sports and being in contact with nature (β = 0.205; p < 0.01) also has a positive effect on the tourist perceiving SDI. These are the tourists with the minor probability to perceive SDI. However, the motivations to know new and different places and to escape from the daily routine do not have an influence on SDI.
Furthermore, the relationship between the nationality of the tourists and their perception of SDI was analyzed. Here, positive relations were revealed with the majority of the markets: Germany, Austria, Belgium, Spain, Russia, France, Netherlands, Ireland, Italy, Luxembourg, Norway, Poland, Portugal, United Kingdom, and Czech Republic. Therefore, the Canary Islands are more likely to be perceived as an SDI by tourists from these countries, whereas the nationalities of Denmark, Finland and Sweden were found to be nonsignificant. Attending to the differences between countries, it could be confirmed that the nationalities with a minor perception of sustainability are the Austrians, the Dutch, and those from Luxembourg. However, the Russians are those who, only because they are of this nationality, are more likely to perceive the destination as sustainable. The greatest value in the case of Russians can be explained by the fact that Russia could be considered as not being a typical European country and, further, that the preferences and experience of Russian tourists differ strikingly from those of tourists of the other European countries [79]. Those results give weight to the concept that national culture influences the way tourists from different countries interpret the sustainability and its fundamental role in the formation of sustainability image of tourism destinations [30].
The results found that age and level of studies determine SDI. The results show, in line with Baloglu and McCleary (1999) [31] and Calantone et al. (1989) [65], that the older a person is, the greater is the likelihood that the individual will perceive SDI (β = 0.163; p < 0.01). On the other hand, the relationship between the mean studies level of a tourist and SDI is negative (β = 0.140; p < 0.01).

5. Discussion

The theoretical implication of this study lies in presenting a comprehensive understanding of factors influencing an SDI. More specifically, the model uses destination primary and secondary images, motivations, cultural background of tourists, and sociodemographic characteristics to explain the perception of SDI. Those variables are crucial in fully understanding the perception of SDI. This means that destination marketing organizations should adjust their strategies to different market segments, attending to the mentioned variables. As far as we are aware, no other researchers have investigated this relationship prior to us.
The more intense the previous experience (primary image) in the destination, the more likely are travelers to have an SDI. This study further suggests that a key determinant of SDI is a destination secondary image. Thus, destination marketing organizations should consider these findings when designing their marketing strategies. The secondary image of a destination could be affected by destinations and the companies operating in the sector through various sources of information such as magazines, tour operators, travel agencies, social media, and so on [80]. DMOs must be able to design strategies in which an image of a sustainable destination is projected since, according to the results of our study, the information that the tourist receives through these sources will influence their perception of a sustainable destination and, consequently, their decision of whether to visit the destination. Those results are in line with the study of Lian and Yu (2019) [81], who highlighted the influence of online information sources in the decision to travel.
Furthermore, the results suggest that three motivational factors (“Fashion, Fun, and Friends”, “Sun, Beach, Relax, and Family”, and “Sports and Nature”) are statistically significant for SDI. Whilst we had hypothesized that a traveler’s motivation to know new and different places and to escape from the daily routine would have a positive effect on the SDI, our findings have revealed that this is not supported. Therefore, destination marketing organizations should project the SDI according to tourists’ motivations [33,82]. Thus, the content used to promote the SDI should be adapted to match tourism motivations. In this way, the possible congruence that exists between the message and the specific motivations of the target market could determine better results [45]. Either way, developing a professional social command centre in charge of managing the social content of the destination seems to be an interesting strategy to foster SDI.
Our findings also suggest that the cultural background of a tourist is an important factor determining SDI. More specifically, our findings reveal that national culture influences the way tourists from different countries interpret sustainability and its fundamental role on the sustainability image of tourism destination formation [30]. This sheds lights on the usefulness of using the nationality as a segmentation criterion, helping marketers to tier customers. DMOs should pay special attention to the markets of The Netherlands, Austria, and Luxembourg, since they are those that have a lower probability of perceiving the destination as sustainable. In markets such as Russia, Spain, Portugal, and Italy, efforts must be aimed at maintaining or even improving the SDI. This is in accordance with the Almeida-Santana et al. (2018) [45] study, which suggests nationality as being a relevant factor when seeking to comprehensively understand the behavior of travelers when choosing their holiday destination.
Furthermore, the results also determined that age and level of studies determine SDI. The results show, in line with Baloglu and McCleary (1999) [31] and Calantone et al. (1989) [65], that the older a person is, the more likely they are to perceive SDI. The negative relationship between the mean study levels expressed by the tourists and SDI is demonstrated. Destination marketing organizations should consider those results in order to better design their marketing strategies. Younger tourists have a lower perception of a sustainable destination, so marketing campaigns aimed at this younger segment should place greater emphasis on the projection of a sustainable destination image. The same approach could be applied to the segment with a high level of studies.
Finally, some limitations of this research are given. This study considers SDI only in respect to the Canary Islands. However, it could be applied to other destinations. SDI could also be further analyzed, with introduction to the model of other factors influencing SDI.

6. Conclusions

This study has focused on seeking to explain the factors that influence the perception of a sustainable destination image by tourists. The importance of carrying out this research is justified by the growing concern shown by tourists about the impact of their activity [83]. DMOs must adapt to the new demands of tourists and design strategies that allow them to position themselves as a sustainable destination if they want to remain competitive in this day and age in which sustainability is fundamental [83].
In order to achieve the aims of this study, information was collected from tourists from 18 European countries who have visited the Canary Islands. This is presented as an appropriate destination to study sustainability [70,71,72,73].
The findings of this research confirm that the primary and secondary images of the destination, the travel motivations of tourists, and their nationality, as well as their age and level of studies influence their perception of SDI. This gives emphasis to the importance of segmentation in the design of destination marketing strategies to position the destination as sustainable.

Author Contributions

All authors made a proportional contribution.

Funding

This research received no external funding.

Acknowledgments

This research and the APC was funded by the Ministerio de Economía, Industria y Competitividad ECO2017-82842-R and by the Canarian Agency for Research, Innovation, and Information Society (ACIISI) cofinanced by the European FEDER Fund under project 2017010116.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Költringer, C.; Dickinger, A. Analyzing destination branding and image from online sources: A web content mining approach. J. Bus. Res. 2015, 68, 1836–1843. [Google Scholar] [CrossRef]
  2. Gallarza, M.G.; Saura, I.G.; Garcı́a, H.C. Destination image: Towards a conceptual framework. Ann. Tour. Res. 2002, 29, 56–78. [Google Scholar] [CrossRef]
  3. Moreno-Gil, S.; Martín-Santana, J.D. Understanding the image of self-contained and serviced apartments: The case of sun and beach destinations. J. Hosp. Tour. Res. 2015, 39, 373–400. [Google Scholar] [CrossRef]
  4. Baloglu, S.; Mangaloglu, M. Tourism Destination Images of Turkey, Egypt, Greece, and Italy as Perceived by US-Based Tour Operators and Travel Agents. Tour. Manag. 2001, 22, 1–9. [Google Scholar] [CrossRef]
  5. Carballo, M.M.; Araña, J.E.; León, C.J.; Moreno-Gil, S. Economic valuation of tourism destination image. Tour. Econ. 2015, 21, 741–759. [Google Scholar] [CrossRef]
  6. Kim, D.; Perdue, R.R. The Influence of Image on Destination Attractiveness. J. Travel Tour. Mark. 2011, 225–239, 225–239. [Google Scholar] [CrossRef]
  7. Almeida-Santana, A.; Moreno-Gil, S. Understanding tourism loyalty: Horizontal vs. destination loyalty. Tour. Manag. 2018, 65, 245–255. [Google Scholar] [CrossRef]
  8. Bigne, J.E.; Sanchez, M.I.; Sanchez, J. Tourism image, evaluation variables and after purchase behaviour: Inter-relationship. Tour. Manag. 2001, 22, 607–616. [Google Scholar] [CrossRef]
  9. Pulido-Fernández, J.; López-Sánchez, Y. Are tourists really willing to pay more for sustainable destinations? Sustainability 2016, 8, 1240. [Google Scholar] [CrossRef]
  10. Weeden, C. Responsible and Ethical Tourist Behaviour; Routledge: London, UK, 2013. [Google Scholar]
  11. Miller, G. Consumerism in sustainable tourism: A survey of UK consumers. J. Sustain. Tour. 2003, 1, 17–39. [Google Scholar] [CrossRef]
  12. Yeoman, I. Tomorrow’s Tourist: Scenarios & Trends; Elsevier: Oxford, UK, 2008. [Google Scholar]
  13. Boniface, B.; Coope, C. Worldwide Destinations Casebook—The Geography of Travel and Tourism; Elsevier Butterworth-Heinemann: Burlington, MA, USA, 2005. [Google Scholar]
  14. Rheem, C. PhoCusWright’s Going Green: The Business Impact of Environmental Awareness on Travel; PhocusWright: Sherman, CT, USA, 2008. [Google Scholar]
  15. Adlwarth, W. Corporate social responsibility: Customer expectations and behavior in the tourism sector. In Trends and Issues in Global Tourism 2010; Conrady, R., Buck, M., Eds.; Springer: Heidelberg/Berlin, Germany, 2010. [Google Scholar]
  16. Dodds, R.; Graci, S.R.; Holmes, M. Does the tourist care? A comparison of tourists in Koh Phi Phi, Thailand and Gili Trawangan, Indonesia. J. Sustain. Tour. 2010, 18, 207–222. [Google Scholar] [CrossRef]
  17. Hedlund, T. The impact of values, environmental concern, and willingness to accept economic sacrifices to protect the environment on tourists’ intentions to buy ecologically sustainable tourism alternatives. Tour. Hosp. Res. 2011, 11, 278–288. [Google Scholar] [CrossRef]
  18. Edgel, S.D.L. Managing Sustainable Tourism: A Legacy for the Future; Haworth Hospitality Press: New York, NY, USA, 2006. [Google Scholar]
  19. Echtner, C.M.; Ritchie, J.B. The meaning and measurement of destination image. J. Tour. Stud. 1991, 2, 2–12. [Google Scholar]
  20. Beerli, A.; Martin, J.D. Factors influencing destination image. Ann. Tour. Res. 2004, 31, 657–681. [Google Scholar] [CrossRef]
  21. Pike, S. Destination image analysis—A review of 142 papers from 1973 to 2000. Tour. Manag. 2002, 23, 541–549. [Google Scholar] [CrossRef]
  22. Kim, S.S.; Morrison, A.M. Changes of images of South Korea among foreign tourists after the 2002 FIFA World Cup. Tour. Manag. 2005, 26, 233–247. [Google Scholar] [CrossRef]
  23. Blažević, B.; Peršić, M. Turistička Regionalizacija u Globalnim Procesima; Fakultet za Turistički i Hotelski Menadžment: Opatija, Croatia, 2009. [Google Scholar]
  24. Pearce, D. Destination management in New Zealand: Structures and functions. J. Destin. Mark. Manag. 2015, 4, 112. [Google Scholar] [CrossRef]
  25. San Martín, H.; Del Bosque, I.A.R. Exploring the cognitive–affective nature of destination image and the role of psychological factors in its formation. Tour. Manag. 2008, 29, 263–277. [Google Scholar] [CrossRef]
  26. Hallmann, K.; Zehrer, A.; Müller, S. Perceived destination image: An image model for a winter sports destination and its effect on intention to revisit. J. Travel Res. 2015, 54, 94–106. [Google Scholar] [CrossRef]
  27. Stylidis, D.; Shani, A.; Belhassen, Y. Testing an integrated destination image model across residents and tourists. Tour. Manag. 2017, 58, 184–195. [Google Scholar] [CrossRef]
  28. Moreno Gil, S.; Ritchie, B.J.; Almeida-Santana, A. Museum tourism in Canary Islands: Assessing image perception of Directors and Visitors. Mus. Manag. Curatorship 2019, 1–20. [Google Scholar] [CrossRef]
  29. Phelps, A. Holiday destination image—The problem of assessment: An example developed in Menorca. Tour. Manag. 1986, 7, 168–180. [Google Scholar] [CrossRef]
  30. de Souza, A.G.; de Farias, S.A.; de Brito, M.P. Cultural dimensions and image: An essay on the impacts of masculinity and individualism on the interpretation of the sustainability of tourism destinations. Rev. Bras. Pesqui. Em Tur. 2014, 8, 238–260. [Google Scholar]
  31. Baloglu, S.; McCleary, K.W. A model of destination image formation. Ann. Tour. Res. 1999, 26, 868–897. [Google Scholar] [CrossRef]
  32. Wehrli, R.; Priskin, J.; Schaffner, D.; Schwarz, J.; Stettler, J. Do Sustainability Experienced Travellers Prefer a More Rational Communication of the Sustainability of a Tourism Product; Hochschule Luzern-Wirtschaft, ITW Institut für Tourismuswirtschaft: Luzern, Switzerland, 2013. [Google Scholar]
  33. Li, M.; Cai, L.A.; Lehto, X.Y.; Huang, J. A missing link in understanding revisit intention—The role of motivation and image. J. Travel Tour. Mark. 2010, 27, 335–348. [Google Scholar] [CrossRef]
  34. Crompton, J.L. Motivations for pleasure vacation. Ann. Tour. Res. 1979, 6, 408–424. [Google Scholar] [CrossRef]
  35. Dann, G.M. Anomie, ego-enhancement and tourism. Ann. Tour. Res. 1977, 4, 184–194. [Google Scholar] [CrossRef]
  36. Baloglu, S. A path analytic model of visitation intention involving information sources, socio-psychological motivations, and destination image. J. Travel Tour. Mark. 2000, 8, 81–90. [Google Scholar] [CrossRef]
  37. Bieger, T.; Laesser, C. Market segmentation by motivation: The case of Switzerland. J. Travel Res. 2002, 41, 68–76. [Google Scholar] [CrossRef]
  38. Chen, G.; Bao, J.; Huang, S. Segmenting Chinese backpackers by travel motivations. Int. J. Tour. Res. 2014, 16, 355–367. [Google Scholar] [CrossRef]
  39. Sung, Y.K.; Chang, K.C.; Sung, Y.F. Market segmentation of international tourists based on motivation to travel: A case study of Taiwan. Asia Pac. J. Tour. Res. 2016, 21, 862–882. [Google Scholar] [CrossRef]
  40. Park, D.B.; Yoon, Y.S. Segmentation by motivation in rural tourism: A Korean case study. Tour. Manag. 2009, 30, 99–108. [Google Scholar] [CrossRef]
  41. Awaritefe, O.D. Destination environment quality and tourists’ spatial behaviour in Nigeria: A case study of third world tropical Africa. Int. J. Tour. Res. 2003, 5, 251–268. [Google Scholar] [CrossRef]
  42. Awaritefe, O.D. Destination image differences between prospective and actual tourists in Nigeria. J. Vacat. Mark. 2004, 10, 264–281. [Google Scholar] [CrossRef]
  43. Keng, K.A.; Cheng, J.L.L. Determining tourist role typologies: An exploratory study of Singapore vacationers. J. Travel Res. 1999, 37, 382–390. [Google Scholar] [CrossRef]
  44. De Mooij, M.; Hofstede, G. Cross-cultural consumer behavior: A review of research findings. J. Int. Consum. Mark. 2011, 23, 181–192. [Google Scholar]
  45. Almeida-Santana, A.; Moreno-Gil, S.; Boza-Chirino, J. The paradox of cultural and media convergence. Segmenting the European tourist market by information sources and motivations. Int. J. Tour. Res. 2018, 20, 613–625. [Google Scholar] [CrossRef]
  46. Budeva, D.G.; Mullen, M.R. International market segmentation: Economics, national culture and time. Eur. J. Mark. 2014, 48, 1209–1238. [Google Scholar] [CrossRef]
  47. Tkaczynski, A.; Rundle-Thiele, S.R.; Beaumont, N. Segmentation: A tourism stakeholder view. Tour. Manag. 2009, 30, 169–175. [Google Scholar] [CrossRef]
  48. Hofstede, G. Culture and organizations. Int. Stud. Manag. Organ. 1980, 10, 15–41. [Google Scholar] [CrossRef]
  49. Crotts, J.C.; Erdmann, R. Does national culture influence consumers’ evaluation of travel services? A test of Hofstede’s model of cross-cultural differences. Manag. Serv. Qual. Int. J. 2000, 10, 410–419. [Google Scholar] [CrossRef]
  50. Hudson, S.; Wang, Y.; Gil, S.M. The influence of a film on destination image and the desire to travel: A cross-cultural comparison. Int. J. Tour. Res. 2011, 13, 177–190. [Google Scholar] [CrossRef]
  51. Muskat, B.; Muskat, M.; Richardson, A. How do Europeans travel in Australia? Examining cultural convergence in travel behaviour. J. Vacat. Mark. 2014, 20, 55–64. [Google Scholar] [CrossRef]
  52. Thrane, C.; Farstad, E. Nationality as a segmentation criterion in tourism research: The case of international tourists’ expenditures while on trips in Norway. Tour. Econ. 2012, 18, 203–217. [Google Scholar] [CrossRef]
  53. Frías, D.M.; Rodríguez, M.A.; Alberto Castañeda, J.; Sabiote, C.M.; Buhalis, D. The formation of a tourist destination’s image via information sources: The moderating effect of culture. Int. J. Tour. Res. 2012, 14, 437–450. [Google Scholar] [CrossRef]
  54. Kim, B. Prideaux Marketing implications arising from a comparative study of international pleasure tourist motivations and other travel-related characteristics of visitors to Korea. Tour. Manag. 2005, 26, 347–357. [Google Scholar] [CrossRef]
  55. Kozak, M. Comparative assessment of tourist satisfaction with destinations across two nationalities. Tour. Manag. 2001, 22, 391–401. [Google Scholar] [CrossRef]
  56. Andersen, O.; Øian, H.; Aas, Ø.; Tangeland, T. Affective and cognitive dimensions of ski destination images. The case of Norway and the Lillehammer region. Scand. J. Hosp. Tour. 2018, 18, 113–131. [Google Scholar] [CrossRef]
  57. de la Hoz-Correa, A.; Muñoz-Leiva, F. The role of information sources and image on the intention to visit a medical tourism destination: A cross-cultural analysis. J. Travel Tour. Mark. 2019, 36, 204–219. [Google Scholar] [CrossRef]
  58. Ko, S.; Lee, T.; Yoon, H.; Kwon, J.; Mather, M. How does context affect assessments of facial emotion? The role of culture and age. Psychol. Aging 2011, 26, 48. [Google Scholar] [CrossRef]
  59. Lee, G.; Lee, C.K. Cross-cultural comparison of the image of Guam perceived by Korean and Japanese leisure travelers: Importance–performance analysis. Tour. Manag. 2009, 30, 922–931. [Google Scholar] [CrossRef]
  60. Min, K.S.; Martin, D.; Jung, J.M. Designing advertising campaigns for destinations with mixed images: Using visitor campaign goal messages to motivate visitors. J. Bus. Res. 2013, 66, 759–764. [Google Scholar] [CrossRef]
  61. Obenour, W.; Lengfelder, J.; Groves, D. The development of a destination through the image assessment of six geographic markets. J. Vacat. Mark. 2005, 11, 107–119. [Google Scholar] [CrossRef]
  62. Agarwal, J.; Malhotra, N.K.; Bolton, R.N. A cross-national and cross-cultural approach to global market segmentation: An application using consumers’ perceived service quality. J. Int. Mark. 2010, 18, 18–40. [Google Scholar] [CrossRef]
  63. Cleveland, M.; Papadopoulos, N.; Laroche, M. Identity, demographics, and consumer behaviors: International market segmentation across product categories. Int. Mark. Rev. 2011, 28, 244–266. [Google Scholar] [CrossRef]
  64. Baloglu, S. The relationship between destination images and sociodemographic and trip characteristics of international travellers. J. Vacat. Mark. 1997, 3, 221–233. [Google Scholar] [CrossRef]
  65. Calantone, R.; Di Benetton, C.; Hakam, A.; Bojanic, D. Multiple multinational tourism positioning using correspondence analysis. J. Travel Res. 1989, 28, 25–32. [Google Scholar] [CrossRef]
  66. World Tourism Organization. International Tourism Highlights, 2019 ed. UNWTO: Madrid, Spain, 2019. [CrossRef]
  67. Bramwell, B. Mass Tourism, Diversification and Sustainability in Southern Europe’s Coastal Regions. In Coastal Mass Tourism: Diversification and Sustainable Development in Southern Europe; Bramwell, B., Ed.; Channel View: Bristol, UK, 2004; pp. 1–31. [Google Scholar]
  68. Jimenez, F.; García Quesada, M.; Villoria, M. Corruption in Paradise: The puzzling case of Lanzarote. In Proceedings of the XXII Pisa World Congress of Political Science, Canary Islands, Spain, 9 July 2012. [Google Scholar]
  69. Santana-Talavera, A.; Fernández-Betancort, H. Times of Tourism: Development and Sustainability in Lanzarote, Spain. In Tourism as an Instrument for Development: A Theoretical and Pracitcal Study; Fayos-Solà, E., Ed.; Emerald: Bingley, UK, 2014; pp. 241–264. [Google Scholar]
  70. Eckert, C.; Pechlaner, H. Alternative product development as strategy towards sustainability in tourism: The case of Lanzarote. Sustainability 2019, 11, 3588. [Google Scholar] [CrossRef]
  71. González-Morales, O.; Talavera, A. CSR as a strategy for public-private relationships in protected island territories: Fuerteventura, Canary Islands. Isl. Stud. J. 2019, 14. [Google Scholar] [CrossRef]
  72. Pérez, F.; Martín, R.; Trujillo, F.; Díaz, M.; Mouhaffel, A. Consumption and Emissions Analysis in Domestic Hot Water Hotels. Case Study: Canary Islands. Sustainability 2019, 11, 599. [Google Scholar] [CrossRef]
  73. Uche-Soria, M.; Rodríguez-Monroy, C. An Efficient Waste-To-Energy Model in Isolated Environments. Case Study: La Gomera (Canary Islands). Sustainability 2019, 11, 3198. [Google Scholar] [CrossRef]
  74. Fodness, D. Measuring tourist motivation. Ann. Tour. Res. 1994, 21, 555–581. [Google Scholar] [CrossRef]
  75. Hair, J.; Babin, B.; Money, A.; Samouel, P. Fundamentos de Métodos de Pesquisa em Administração; Bookman Companhia Ed: Sao Paulo, Brazil, 2005. [Google Scholar]
  76. Meyers, L.S.; Gamst, G.; Guarino, A.J. Data screening. In Applied Multivariate Research-Design and Interpretation; SAGE: Newcastle upon Tyne, UK, 2006. [Google Scholar]
  77. Beerli, A.; Martı́n, J.D. Tourists’ characteristics and the perceived image of tourist destinations: A quantitative analysis—A case study of Lanzarote, Spain. Tour. Manag. 2004, 25, 623–636. [Google Scholar] [CrossRef]
  78. Chen, R.S.; Tsai, C.C. Gender differences in Taiwan university students’ attitudes toward web-based learning. Cyberpsychol. Behav. 2007, 10, 645–654. [Google Scholar] [CrossRef] [PubMed]
  79. Whang, H.; Yong, S.; Ko, E. Pop culture, destination images, and visit intentions: Theory and research on travel motivations of Chinese and Russian tourists. J. Bus. Res. 2016, 69, 631–641. [Google Scholar] [CrossRef]
  80. Marine-Roig, E.; Ferrer-Rosell, B. Measuring the gap between projected and perceived destination images of Catalonia using compositional analysis. Tour. Manag. 2018, 68, 236–249. [Google Scholar] [CrossRef]
  81. Lian, T.; Yu, C. Impacts of online images of a tourist destination on tourist travel decision. Tour. Geogr. 2019, 1–30. [Google Scholar] [CrossRef]
  82. Hernández-Mogollón, J.; Duarte, P.; Folgado-Fernández, J. The contribution of cultural events to the formation of the cognitive and affective images of a tourist destination. J. Destin. Mark. Manag. 2018, 8, 170–178. [Google Scholar] [CrossRef]
  83. Hanna, P.; Font, X.; Scarles, C.; Weeden, C.; Harrison, C. Tourist destination marketing: From sustainability myopia to memorable experiences. J. Destin. Mark. Manag. 2018, 9, 36–43. [Google Scholar] [CrossRef]
Table
Table 1. Description of the variables included in the model.
Table 1. Description of the variables included in the model.
CategoryVariablesDefinition
Sociodemographic and geographic variables AgeA continuous variable that explains the age of the individuals in years
GenderDichotomic variables that take 0 as a value when the individual is male and 1 when is female
Years of study Number of years of study
Germany, Austria, Belgium, Denmark, Spain, Russia, Finland, France, Netherlands, Ireland, Italy, Luxembourg, Norway, Poland, Portugal, United Kingdom, Czech Republic, SwedenDichotomic variables that take 0 as a value when the individual does not belong to one of the nationalities under study and 1 when they do
Motivation variables Fodness Scale (1994) [74]. See Table 2Scale of 1 to 7 (very negative image to very positive image)
Behavioral characteristics (Primary and secondary images)Number of times a destination is visitedA continuous variable that explains the number of visits to Canary Islands
Last year visitedNumber of years since the last visit
Has seen advertising about the destinationDichotomic variables that take 0 as a value when the individual has seen advertising about the destination and 1 when they have not
EndogenousSustainable Destination Image (SDI)Dichotomic variables that take 0 as a value when the individual has not perceived a sustainable image and 1 when they have
Table
Table 2. Motivation factor analysis.
Table 2. Motivation factor analysis.
VariablesMOT1MOT2MOT3MOT4Cronbach´s Alpha
To go to places that are fashionable0.738 0.560
To look for entertainment and fun0.688
To enjoy and spend time with friends0.479
To rest and relax 0.772 0.623
To spent time in a destination with good beaches and pleasant climate 0.654
To enjoy and spend time with family 0.611
To go to comfortable places 0.495
To do sports 0.834 0.692
To be in contact with nature 0.692
To do watersports 0.636
To do exciting things 0.487
To know new and different places 0.7800.413
To escape from daily routine 0.545
Cronbach´s alpha 0.768
% Explained variance: 55.933
KMO: 0.806
Bartlett: 49379.541
Significance: 0.000
Table
Table 3. Estimated binomial logit model.
Table 3. Estimated binomial logit model.
Sustainable Destination Image
βεPercent Change in the Odds
Number of times a destination is visited0.004 ***0.0010.4
Last year visited0.200 ***0.02322.1
Has seen advertising about the destination0.187 ***0.06120.5
MOT1: Fashion, Fun, and Friends0.365 ***0.03344.0
MOT2: Sun, Beach, Relax, and Family0.244 ***0.03127.7
MOT3: Sports and Nature0.205 ***0.03122.7
MOT4: Knowledge---
Germany0.753 ***0.160112.4
Austria0.457 **0.18557.9
Belgium0.867 ***0.184138.0
Denmark---
Spain2.171 ***0.171776.9
Russia2.637 ***0.3121296.4
Finland---
France0.906 ***0.203147.4
Netherlands0.452 ***0.16857.1
Ireland1.262 ***0.168253.1
Italy1.814 ***0.205513.7
Luxembourg0.592 **0.25980.8
Norway0.822 ***0.172127.6
Poland1.745 ***0.234472.6
Portugal1.836 ***0.214526.9
United Kingdom1.102 ***0.163201.0
Czech Republic0.973 ***0.239164.5
Sweden---
Age0.163 ***0.02917.7
Gender---
Education−0.140 ***0.031−13
Constant−1.690 ***0.197
−2 Log likelihood6815.447
Note: *** 0.01%; ** 0.05%.
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