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This contribution conducts a mini-review of the topic Horizontal Loyalty based on the paper written by Almeida and Moreno (2018).
The traditional analysis of loyalty centred on a single destination and with a one-dimensional perspective has recently been questioned. This study analyses horizontal loyalty, and explains the factors that determine this behavior. This paper also identifies the differences between the variables that explain horizontal loyalty and the loyalty to a single destination. This study is the first empirical application of this focus to a tourist destination. The results help to understand the necessary change of focus in the study of loyalty in the tourist context, as well as in the design of strategies, where the emphasis should be placed on tourists. This way, destinations will be able to improve their competitiveness.
Keywords: Horizontal Loyalty, Coopetition, Competitiveness, Segmenting Image Motivations.
SIGNIFICANCE/IMPLICATIONS FOR THEORY AND PRACTICE
Traditionally, research into loyalty in a tourist destination context has focused its attention on how a destination relates to tourists to try to establish lasting and beneficial relationships with them. However, less attention has been paid to the study from the perspective of tourists and how these relate to destinations (Araña et al., 2016). In order to allow destinations to be able to improve their marketing strategies and tourist loyalty, a change of focus is absolutely necessary (Font & Villarino, 2015; Nordbø, Engilbertsson & Vale, 2014). “Service-dominant logic”, as articulated by Lusch & Vargo (2006), claims for a customer-centered focus, where the context of creating value takes ground in networks of networks (destinations and tourists in this case). Focusing on tourists and how they establish their loyalty relationships with different destinations will help to understand how destinations should relate to both tourists and competitors, and it may be beneficial to foster coopetition between tourist destinations to improve competitiveness of the same.
Increasing competition among tourist destinations is a significant trend (Mariani & Baggio, 2012). This is accentuated by a larger number of holidays, albeit shorter ones, per individual, together with the unstoppable growth of the number of destinations in the market and the development of their offer (UNWTO, 2013), which make this change in focus even more necessary in the analysis of tourist loyalty. While some tourists may be loyal to a single destination, there are a large number that share out holidays between different destinations, which may cooperate and/or compete with each other. In the current tourism scenario, destinations are forced to increase their competitiveness, and literature shows that collaboration and cooperation between tourist destinations (Fyall, Garrod & Wang, 2012; David et al., 2018), as well as the development of loyalty (Weaver & Lawton, 2011) are relevant strategies for destinations in achieving competitive advantages in the long term. Therefore, it is necessary to further analyse this phenomenon.
ORIGINALITY AND INNOVATION
Loyalty is a construct that has been tackled in literature in a very homogeneous way and all the different ways in which tourists can show their loyalty have not been contemplated. According to McKercher, Denizci-Guillet & Ng (2012), most studies on loyalty in the tourism industry focus on a single unit of analysis (e.g. a single destination), and apply similar indicators, which shows a lack of conceptual and methodological innovation. Specifically, according to these authors, from the consumer perspective, one can speak of the existence of horizontal loyalty – HL (Almeida & Moreno, 2017) where tourists can be loyal to more than one supplier occupying the same level within the tourism system. Thus, tourists can show their loyalty to several destinations at the same time.
The study of HL, which is hardly explored in tourism literature, requires an alternative methodological approach and suggests a better knowledge of the tourist and an answer to the following question: What factors really explain the differences between HL and single-destination loyalty (DL)? In literature, serious efforts have been made to investigate the factors that influence customer loyalty (Han, Hyun & Kim, 2014), but there are no studies that analyse the factors that determine whether a tourist is loyal to multiple destinations. Thus, the objective of this research is to segment tourists according to the way in which they manifest their loyalty to tourist destinations and to analyse whether or not the factors that determine HL are the same as those that determine DL.
Europe remains the world's largest outbound tourism region, generating more than half of global international arrivals per year (UNWTO, 2016). For this reason, the target population of this study was European tourists, aged 16 and over, from 17 of the main outbound European countries in terms of tourists: Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Norway, Poland, Portugal, Spain, Sweden, Switzerland, the Netherlands and the United Kingdom.
The work was done through Computer-Assisted Web Interviewing (CAWI), to a representative sample of the 16 mentioned countries, from a database of panelists in each country. A random selection was made based on the variables of stratification of geographical area and province, on the one hand, and, on the other, of gender and age, in order to guarantee the representativeness of the sample with the population of each country. Once the questionnaire was translated and pre-tested in the language of the potential tourists, and the relevant corrections were made in those questions that raised difficulties of comprehension, the fieldwork was carried out. The defined sample was of 8,500 tourists (500 in each country) and the actual sample obtained of 6,964 tourists, between 400 and 459 tourists per country. The selected sample was sent a personalised email inviting them to participate in the study, with a link in the mail that led them to the online survey. In order to ensure the expected number of surveys, during the three months of fieldwork in different countries, two reminders were held to encourage response.
After completing the fieldwork and having applied the corresponding quality controls, we performed a binomial Logit analysis with the latest version of the SPSS statistical analysis programme. In this case a Logit model based on the theory of random utility has been chosen. The use of this model guarantees robustness in the estimated results and the fulfilment of the properties of the conventional utility functions established by the theory of the consumer.
In this case, the 7 islands (destinations) that compose the Canary Islands are considered the competitive set: Tenerife, Gran Canaria, Lanzarote, Fuerteventura, La Palma, La Gomera, and El Hierro. This destination was chosen, as well as for convenience, as a well-known European leading destination (Gil, 2003) and because there is an interesting complementarity between the islands that makes it ideal for the study of HL. Two groups of tourists are differentiated, those that show DL and those that manifest HL. A tourist can be defined as being loyal to a single destination if at least two or more visits to the same destination are observed, without observing other visits to the rest of destinations considered in the competitive set (a single island of the Canary Islands in two occasions or more, and no other). On the other hand, tourists are considered to be HL tourists when they have visited at least two different destinations in the group (at least two islands among the seven Canary Islands).
DATA AND FINDINGS
A review of literature helped to conceptualise the subject of study: the loyalty to the destination and its fundamental dimensions, different groups of tourists were identified according to the type of loyalty shown: loyalty to a destination and horizontal loyalty to multiple destinations. Subsequently, the differences in their explanatory variables were analysed with a methodological design based on a questionnaire made to potential tourists from 17 countries, with a large sample size (6,964 tourists) that allowed consistent conclusions to be drawn (Figure 1). The results allowed us to identify the existence of variables that influence both types of loyalty, and furthermore, that there are others that influence HL and not DL and vice versa. In this way, when designing marketing strategies and tourist loyalty, managers should take into account the differences between the determinants of each type of loyalty.
Regarding the theoretical implications, the present study supposes the first empirical application of the factors that determine HL, and its differences with DL, focused on tourist destinations, where the concept of loyalty has its peculiarities (Alegre & Juaneda, 2006). Thus, the need for a change of focus in the study of loyalty in the context of tourist destinations is highlighted, where future work could use the methodology and conclusions that are developed in the present research. Traditionally, destinations and their marketing strategies have been analysed without taking into account other tourist destinations, or the relationship of tourists with all of them. This study proposes a change of vision in the design of such strategies, where the emphasis is placed on the community of tourists and how these relate to many destinations.
On the other hand, the practical implications are obvious, since the understanding of the differences raised in the loyalty of the tourist implies different marketing strategies for each group, allowing the destinations to enhance their competitiveness. Thus, destination organisations and managers of companies operating in the sector could maximise their available resources for tourism promotion and could also establish possible joint marketing strategies.
Specifically, the fact that the higher the age and the level of income of the tourist influences both the HL and the DL, means that the destinations must design loyalty programmes especially directed to these segments, being able to work with partners where this profile (higher age and income level) is the most common (e.g. airline loyalty programmes). As for the negative effect of the sun and beach image on both types of loyalty, this denotes the need for innovation by these destinations, even with the intention to “get out of the category” of sun and beach through innovation and differentiation if they want to keep tourists loyal. In this line, the identification of two factors in the affective image suggests further studying a new paradigm of the sun and beach image of destinations (affective image of authenticity, well-being and sustainability). Likewise, the projected image of its general infrastructures and leisure, to the extent that they are congruent with that of the markets of origin, are also a good impulse for loyalty. In any case, social media are an ideal source for communicating all these proposals, as they promote both DL and HL.
In the case of destinations that want to promote DL, in addition to the previous aspects, the projection of an image aimed at those tourists motivated by a fashionable and prestigious destination, which allows social exhibitionism, would seem to be an appropriate strategy, moving away from a cheerful and stimulating destination image, as an image shared with other places. On the other hand, to promote HL, competing destinations can carry out joint promotional actions that help them in the conversion of the intention to visit, working on a shared global image based on common aspects of their environmental situation. In addition, as a means of avoiding the tourist’s search for something new and lack of loyalty, destinations can continually renew their attractions, in addition to being able to offer joint proposals and itinerant events between the competing group.
Finally, some lines of future research are suggested: a) in the first place and since this study has focused only on a geographical area and a competitive set, the set of considered destinations can be expanded. For example, in the once-in-a-lifetime destinations, the extent to which these conclusions apply and whether they can also be networked should be analysed; Furthermore, other additional indicators may be considered to help explain the visits to each of the different destinations (satisfaction, quality, familiarity, cultural differences, etc.), and incorporate vertical and experiential loyalty dimensions; Analyse if the order in which the different destinations are visited influences HL and the determination of the number of times the group of competing destinations is visited; To further analyse the different typologies of social media and sources of information used by tourists to find out about their travel destination in the determination of HL and; To evaluate loyalty from a social, environmental and economic perspective, in its different dimensions (DL, HL) and its implications in the brand architecture, which would allow to evaluate the promotional proposals with better criteria.
Alegre, J. & Juaneda, C. (2006). Destination loyalty: Consumers’ economic behavior. Annals of Tourism Research, 33(3), 684-706.
Almeida-Santana, A. & Moreno-Gil, S. (2017). New trends in information search and their influence on destination loyalty: Digital destinations and relationship marketing. Journal of Destination Marketing & Management, 6(2), 150-161.
Almeida-Santana, A. & Moreno-Gil, S. (2018). Understanding tourism loyalty: Horizontal vs. destination loyalty. Tourism Management, 65(2018), 245-255.
Araña, J., León, C., Carballo, M. & Moreno, S. (2016). Designing tourist information offices: The role of the human factor. Journal of Travel Research, 55(6), 764-773.
David-Negre, T., Almedida-Santana, A., Hernández, J.M. & Moreno-Gil, S. (2018). Understanding European tourists’ use of e-tourism platforms. Analysis of networks. Information Technology & Tourism, 20(1-4), 131-152.
Font, X. & Villarino, J. (2015). Sustainability marketing myopia: The lack of sustainability communication persuasiveness. Journal of Vacation Marketing, 21(4), 326-335.
Fyall, A., Garrod, B. & Wang, Y. (2012). Destination collaboration: A critical review of theoretical approaches to a multi-dimensional phenomenon. Journal of Destination Marketing & Management, 1(1), 10-26.
Gil, S.M. (2003). Tourism development in the Canary Islands. Annals of Tourism Research, 30(3), 744-747.
Han, H., Hyun, S.S. & Kim, W. (2014). In-flight service performance and passenger loyalty: A cross-national (China/Korea) study of travelers using low-cost carriers. Journal of Travel and Tourism Marketing, 31(5), 589-609.
Lusch, R.F. & Vargo, S.L. (2006). Service-dominant logic: Reactions, reflections and refinements. Marketing Theory, 6(3), 281-288.
Mariani, M.M. & Baggio, R. (2012). Special issue: Managing tourism in a changing world: Issues and cases. Anatolia, 23(1), 1-3.
McKercher, B., Denizci-Guillet, B. & Ng, E. (2012). Rethinking loyalty. Annals of Tourism Research, 39(2), 708-734.
Nordbø, I., Engilbertsson, H.O. & Vale, L.S.R. (2014). Market myopia in the development of hiking destinations: The case of Norwegian DMOs. Journal of Hospitality Marketing & Management, 23(4), 380-405.
UNWTO. (2016). Tourism Highlights. Available at: http://www2.unwto.org/en
UNWTO. (2013). Annual Report. Available at: http://www2.unwto.org/en
Weaver, D.B. & Lawton, L.J. (2011). Visitor loyalty at a private South Carolina protected area. Journal of Travel Research, 50(3), 335-346.