Antecedents of loyalty intentions among young adult tourists: A survey

Wąsowicz-Zaborek, Elżbieta Article Antecedents of loyalty intentions among young adult tourists: A survey International Journal of Management and Economics Provided in Cooperation with: SGH Warsaw School of Economics, Warsaw Suggested Citation: Wąsowicz-Zaborek, Elżbieta (2019) : Antecedents of loyalty intentions among young adult tourists: A survey, International Journal of Management and Economics, ISSN 2543-5361, Sciendo, Warsaw, Vol. 55, Iss. 4, pp. 331-345, https://doi.org/10.2478/ijme-2019-0021 This Version is available at: https://hdl.handle.net/10419/309696 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ International Journal of Management and Economics 2019; 55(4): 331–345 Elżbieta Wąsowicz-Zaborek* Antecedents of loyalty intentions among young adult tourists: a survey https://doi.org/10.2478/ijme-2019-0021 Received August 01, 2019; accepted November 14, 2019 Abstract: The purpose of this paper was to examine the antecedents of young adult tourists’ loyalty intentions. The study is concerned with the overall loyalty tendencies of individuals, comprising the two dimensions of revisit intentions (RVIs) and recommendation intentions (RIs), and thus does not explore their loyalty to a specific destination (as in most previous studies). The research uses an Internet questionnaire with a total sample of 305 university students recruited from two Polish universities. Statistical analysis with the partial least squares structural equation modeling method indicates that destination RI is mainly driven by social bonding, while RVI is influenced positively by risk and uncertainty avoidance and negatively by novelty and variety seeking. In addition, income is found to be a significant moderator in the relationship between risk and uncertainty perception and RIs, such that a transition from very low to very high incomes tends to reverse the focal relationship from positive to negative. In addition, the research demonstrates that there is no significant difference between male and female young tourist’s loyalty intention. Implications for tourism entrepreneurs and destinations are suggested in the concluding section of the article. Keywords: loyalty in tourism, destination loyalty, recommendation intention, revisit intention, PLS-SEM JEL Classification: Z32, Z33, M31 1 Introduction One of the attributes of tourism demand is its restitution [Dziedzic and Skalska, 2012], caused by the constant renewal of tourists’ needs. An emerging tourist need may be associated with a desire to repeat a similar trip or may manifest itself in a preference to visit the same location but in a different form or for a different purpose (e.g. different accommodation, meals, different trip organization). Given how widespread this phenomenon is, the issue of loyalty and its determinants becomes particularly relevant in the tourism sector. Customer loyalty is a broad and complex concept. It refers to the overall behavior towards a specific offer, company, product, facility, institution, person or place. Oliver [1997] believes that full loyalty occurs when a customer is deeply convinced that he will buy a particular product again in the future and recommend it, regardless of the market conditions and other contextual factors that may cause a change in their behavior. Seweryn [2012] pointed out that current trends in consumption (hedonism, sublimation, and individualism) may result in a lower inclination to stay loyal. All manifestations of loyalty behavior can have a positive impact and bring benefits to vendors [Reichheld et al., 2000]. Retaining existing customers may be cheaper than acquiring new ones [Fornell and Wernerfelt, 1987]. Loyal customers are also more likely to share positive information about the product with their friends, relatives, and other potential consumers [Foscht et al., 2009]. Meleddu et al. [2015] indicated that the tendency to recommend a tourist product is a result of being satisfied with staying at a destination. At the same time, different elements of Empirical Paper *Corresponding author: Elżbieta Wąsowicz-Zaborek, Collegium of World Economy, SGH Warsaw School of Economics E-mail: ewasow[email protected].pl Open Access. © 2019 Elżbieta Wąsowicz-Zaborek, published by Sciendo. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License. 332 E. Wąsowicz-Zaborek the destination offer may diversely affect the level of satisfaction, and consequently revisit intention (RVI) and share positive information. Therefore, understanding the reasons for tourist loyalty to destinations may help regions and locations compete in an increasingly challenging market [Chen and Gursoy, 2001]. One of the factors differentiating loyalty behavior in tourism may be the age of travelers. Members of different generations tend to demonstrate different willingness to return to places already visited. In this article, the preferences of young adults – the so-called Generation Y – will be investigated. The manuscript presents the results of the author’s own research conducted on a sample of young adults. Constructed on the basis of a literature review, concepts used in the research tool allowed for the estimation of a structural model showing the relationships that exist between the novelty and variety seeking (NVS), uncertainty and risk perception, social bonding (SB), and loyalty inclination expressed through its two dimensions: RVI and intention to recommend the destination. 2 Literature review and hypotheses 2.1 Research gap identification Loyalty is a multi-dimensional concept, and many authors present different approaches to defining its dimensions. Proponents of a one-dimensional approach focus mainly on the volume and repetition of purchases or repeat buying intention [Farley, 1964; Sheth, 1968; McConnell, 1968], which underscores the behavioral facet of the concept. In contrast, Worthington et al. [2009] considered loyalty as a three-dimensional phenomenon encompassing three aspects: –cognitive (cognitive), related to the evaluation of the features of an offer, –affective, relating to the emotions that the product evokes, –behavioral, as an intention to: –buy the same product again, –buy a greater quantity of the same product, and –give a positive opinion about the product. Accordingly, achieving loyalty in the cognitive, affective, and behavioral sense induces lower sensitivity to competitors’ actions and leads to many topand bottom-line benefits for the company [Strum and Thiry, 1991]. Yet another popular perspective identifies two basic dimensions to loyalty: attitudinal and behavioral [Day, 1969], which are also what the author adopted for the current study. The attitudinal dimension views loyalty in terms of consumers’ strength of affection toward a brand [Backman and Crompton, 1991]. When comparing the twoand three-dimensional conceptualizations of loyalty, one can observe that cognitive and affective dimensions can be combined with repurchase intentions to form the attitudinal dimension, while all factual actions are classified as behavioral. Attitudinal loyalty can be measured with product preferences, buying intentions, supplier preferences, and willingness to recommend. Behavioral loyalty is usually operationalized as the frequency and quantity of the repurchase of a product, sometimes supplemented by metrics of other purchasing patterns. Many researches accommodate behavioral and attitudinal aspects of loyalty by using a composite definition of customer loyalty, which is a combination of both [Jacoby and Kyner, 1973; Backman and Crompton, 1991; Oliver, 1999; Chen and Tsai, 2007]. Even though there is lack of research comparing tourists across generations, age is a frequently controlled demographical variable, as individuals of various ages might show differences in loyalty to a tourist destination. There is evidence that older customers (>50years) tend to be more satisfied and more loyal than their younger counterparts [Hsu, 2000], but some studies do not show any meaningful agerelated differences [Chi, 2011]. The current study focuses on the generation of young adults, who, unlike their predecessors, grew up in the age of ubiquitous information and progressive globalization. They have always been accompanied by almost unlimited opportunities to travel and knowledge acquisition and also by an unprecedented variety of options for destinations and travel arrangements. Antecedents of loyalty intentions among young adult tourists 333 Generation Y, also known as the Millennials, is broadly defined as those born between 1980 and 2000 [Richard K. Miller and Associates, 2011]. However, there is no commonly accepted consensus and different authors might use dissimilar timeframes, e.g. 1977–1994 [New Strategist, 2004] or 1982–2005 [Howe and Strauss, 2007]. In Poland, Generation Y is often defined as people of the demographic boom, born in the second part of the 1980s and in the 1990s [Gołąb-Andrzejak, 2014]. Similarly, in this research, the time horizon was set at 1986–2000 and the Millennials aged 18–32years old were studied. Members of Generation Y are characterized as [Moscardo and Benckendorff, 2010; Gołąb-Andrzejak, 2016]: –being well informed about current affairs and trends through their intense use of electronic media, –using the Internet for shopping, –looking for shopping deals, –having relatively low awareness and skills in financial planning, –inclined to extend adolescence with a longer period of formal education, –having a positive attitude toward diversity, flexibility, social issues, and the future, and –oriented toward family and their close social groups (friends and acquaintances). It is important to note that the profile of people born at any given time is determined by the changes in the macro environment. The Polish Generation Y does not remember the times of the People’s Republic of Poland. They grew up in the free market economy with the possibility of traveling without limitations. Sustained rapid economic development has also removed many economic barriers. Therefore, travel is an important part of the leisure time activities of the young adult Poles. There is a dearth of studies on the tourist loyalty behavior of Generation Y. Most researchers investigating loyalty concentrate on frequency of travel [Richards, 2007], travel motivation [Todorović and Jovičić, 2016], or the modes of tour organization and realization [Kowalczyk-Anioł, 2012]. Those who have investigated RVIs studied mainly travel motivations and satisfaction from previous visits [Kozak and Rimmington, 2000; Bigne et al., 2001; Bowen, 2001; Kozak, 2001; Um et al., 2006; Huang and Hsu, 2009; Ramseook-Munhurrun et al., 2015]. As was already mentioned, the overwhelming majority of authors explored loyalty intentions or loyalty behavior in the context of specific, explicitly defined destinations, which lowered validity of any general conclusions about drivers of loyalty [George and George, 2004; Yoon and Uysal, 2005; Chen and Tsai, 2007; Kim and Brown, 2012; Assaker and Hallak, 2013; Artuger and Cetinsoz, 2017] and on Polish tourist market [Seweryn, 2010]. The current study, by measuring overall loyalty intentions separately from any particular place, attempts to provide insights into general loyalty forming patterns. The author did not identify a similar survey conducted on the Polish tourism market on a sample of young adults. 2.2 Destination loyalty intention Loyalty intention toward tourism destinations has been a subject of research and discussion for many authors. There have been numerous attempts to establish models of loyalty to tourist destinations [Kozak, 2001; Oom do Valle et al., 2006; Chi, 2011; Emir et al., 2016; Su et al., 2017; Ribeiro et al., 2018]. Most authors agree on the importance of satisfaction as a key driving factor of loyalty intentions [Duman and Mattila, 2005; Oom do Valle et al., 2006; Chi, 2011; Sabiote et al., 2012; Su et al., 2017; Ribeiro et al., 2018]. Researchers investigating reasons for choosing destinations identified a list of push and pull factors that can increase or decrease loyalty behavior, such as desire to escape, variety seeking, social factors, health recovery, need of rest, health recovery (push), tourist attractions, resources, local culture, local communities, services, shopping and entertainment opportunities, events, and tourist infrastructure (pull) [Kim, 2008; Mechinda et al., 2009; Sato et al., 2016; Wąsowicz-Zaborek, 2017]. The construct loyalty intention can be measured in different ways. In this research, after extensive literature studies, the author decided to use a framework of two main dimensions: re-visit intention (RVI) and recommendation intention (RI). Similar approach can be found in Oppermann [2000], Kozak and Rimmington [2000], Yoon and Uysal [2005], Oom do Valle et al. [2006], Chen and Tsai [2007], Rajesh [2013], Guzman-Parra et al. [2016], Su et al. [2017], and Chi and Qu [2008]. 334 E. Wąsowicz-Zaborek 2.3 Risk and uncertainty perception (RUP) A major factor in the choice of destination, crucial for research on risks and uncertainties, is the difficulty for tourists to anticipate or imagine the situation at a destination before travelling and therefore having to rely on information from sources such as media, friends, relatives, and tourist organizations [Karl, 2018]. Uncertainty avoidance is not the same as risk avoidance [Hofstede, 2011]. Uncertainty is vague and defies calculation, while risk is quantifiable and thus can be considered more consciously. Perception of risk accompanies almost all purchasing decisions through the assessment of benefits and costs connected with the purchase. One way to reduce risk is searching for and collecting information related to purchases, which may lead to increased loyalty to a brand if the choice made was satisfactory. Perceived risk is often an essential factor discouraging from changing the supplier of a product [Lee and Cunningham, 2001]. Perceived risk is established in literature as a potent determinant in the decision-making process of tourists. It is owing to the characteristics of the tourist product, such as its complexity, intangibility, and inseparability of its consumption and creation. Researchers identify several dimensions of risk in tourism: 1) physical, 2) functional, 3) psychological, 4) social, 5) temporal/time, 6) financial, and 7) overall (e.g. Boksberger and Craig-Smith [2006], Fuchs and Reichel [2008], and Çetinsöz and Ege [2013]). Owing to the general nature of this current research and the lack of reference to any specific destination in the survey, the overall dimension and its indicators were used for measurement. Perceived risk related to the choice of a tourism destination may be considerable. An unknown and never visited before destination can be difficult to assess, and thus, the level of uncertainty will be high. In consequence, choosing a well-known destination decreases uncertainty and the perceived risk becomes lower. This close relationship between the concepts of risk and uncertainty and their similar influence on purchasing behavior, as indicated in the literature, led the author to decide to merge the two constructs into one. Hence, the following hypotheses were proposed: H.1 RUP has a positive impact on RI H.2 RUP has a positive impact on RVI 2.4 Novelty and variety seeking The search for variety is an internally motivated behavior, where a change in one’s everyday routine is rewarded with a sense of satisfaction [Niininen and Riley, 2008]. For some people, a daily routine may lead to low stimulation and boredom. Thus, a trip to a new place has a high stimulation potential and can increase one’s level of satisfaction [Bello and Etzel, 1985]. Variety seeking may also manifest itself in traveling to places visited before, but to spend time differently by participating in other activities than previously. Novelty seeking is the difference between a current perception and past experiences. This implies a desire to take physical, psychological, and social risks for the sake of diverse, new and sophisticated experiences [Coudounaris and Sthapit, 2017]. Novelty seeking is particularly important in tourism as it is an important motivation for travel [Duman and Mattila, 2005] and it is an innate feature of some travelers [Lee and Crompton, 1992]. The novelty seeking construct developed by Lee and Crompton [1992] consists of change from routine, thrill, surprise, and boredom alleviation. It can be assumed that tourists motivated by the search for novelty or variety are less likely to visit the same destinations again because such trips will not provide them with sufficient excitement and therefore are boring and can be associated with a waste of time and money. However, being very satisfied with a new trip can make them more willing to recommend the visited place. Thus, the author hypothesizes: H.3 NVS has a positive impact on RI H.4 NVS has a negative impact on RVI Antecedents of loyalty intentions among young adult tourists 335 2.5 Social bonding Low and Altman [1992] note that SB relates to social relationships among individuals, between individuals and communities, and individuals and culture. SB is a construct that is primarily of interest to the literature in the field of environmental psychology as one of proposed dimensions of the place attachment concept [Kyle et al., 2005; Saxena, 2006; Chen et al., 2014]. As place attachment may be a very significant factor influencing tourist destination choice, SB has recently become a more commonly studied construct in the tourism literature [Kyle et al., 2005; Seweryn, 2013]. Strong social relations can lead to strong emotional ties to places, and these emotions are often the product of repetitive interactions and experiences that shape sentiment [Kyle and Chick, 2007]. As a consequence, social relations may cause higher RVI. Furthermore, increasing emotional involvement may influence the willingness to share information about the place to which a tourist is attached. Accordingly, it is possible to posit: H.5 SB has a positive impact on RI H.6 SB has a positive impact on RVI 3 Conceptual framework and research methods Having identified the research gap, the author decided to conduct a survey to collect data from Generation Y members to test the six research hypotheses. In this study, the author models the relationships between destination loyalty dimensions and their antecedents with a framework that involves five composite variables (or constructs): 1) RUP, 2) NVS, 3) SB, 4) RI, and 5) RVI. The links among the variables and pertinent hypotheses are illustrated in Figure 1. Figure 1. Conceptual model and hypotheses of the study. Source: own elaboration. 336 E. Wąsowicz-Zaborek The model indicates that motivations and attitudes of tourists may influence their loyalty behavior. The research purposefully omits the specific features of the visited destination and the tourist’s satisfaction with the stay, which are most frequently studied by other researchers in the context of loyalty. The author’s intention was to determine general factors that might be important when returning to or recommending a destination, having more to do with individual attributes of the tourist rather than the specifics of a particular destination. In order to collect empirical data, an Internet questionnaire was used. It was divided into three parts. The first part included questions about previous tourist experiences and motivation for travels. Questions in this part were constructed using nominal and Likert scales. The second part of the questionnaire referred to the tendency to revisit and to share opinions about the visited place, as well as the reasons for (not) returning to the visited places. Questions were designed with the use of Likert scales. Likert statements used for measuring the constructs are presented in Table 4. The questionnaire concluded with demographical items. The survey was conducted on a group of 305 respondents recruited from the students of the SGH Warsaw School of Economics and the WSB University in Gdańsk from October 2018 to April 2019. All respondents were aged 18–32 years. Groups of students are a common subject of research in the tourism sector (e.g. Michael et al., 2003; Gallarza and Saura, 2006; Kim et al., 2006; Xu et al., 2009; Kim and Park, 2016). This is because this group of young adults is very active in tourism and involved in many tourist trips. It is partly because they have more free time to spend on traveling. They are also involved in many different tourism activities, e.g. active, cultural, educational, and leisure tourism. So, their experiences are very differentiated and potentially interesting for researchers. In addition, most students are unmarried and have no children, which allows them to make purchasing decisions based on their own preferences and likes, without the need to adjust to the needs of other family members. Thus, it can be assumed that the opinions expressed in the research reflect their own needs and not those shaped by the circumstances they find themselves in. Table 1 describes demographical characteristics of the sample. Because of a filter question at the beginning of the questionnaire, all respondents had traveled for tourist purposes at least once in the five years preceding the interview. The vast majority declared traveling both in Poland and abroad (89.2%). A total of 5.6% of respondents traveled only abroad, while 5.2% visited only Polish destinations. Table 1. Descriptive Summary of the Sample (n=305) Demographic n % Gender Female 187 61,3% Male 118 38,7% Size of the place of living village 18 5,9 town up to 50 K 15 4,9 town 51-150 K 15 4,9 City 151 – 500 K 20 6,6 City more than 500 K 237 77,7 Work or Study student 208 68,2 working student 97 31,8 Income very low (difficult to cover maintenance costs) 4 1,3 low 32 10,5 moderate 156 51,1 high 93 30,5 very high 20 6,6 Source: own elaboration Antecedents of loyalty intentions among young adult tourists 337 The initial statistical analysis was performed using SPSS 25. In the second phase, to explore regression paths among variables, SmartPLS 3.2.8 was used. 4 Research results It seems that out of the two dimensions of destination loyalty, respondents are more likely to share opinions (both positive and negative) about visited places than to return to them (see Table 2). This may be related to the popularity of Internet tools and social media among Generation Y, and social media are among the most commonly used channels for sharing opinions about trips and destinations [TripAdvisor, 2016]. Regarding frequency of travel to the same places and not returning to previously visited ones, the average level of indications was similar and relatively low (2.18 and 2.32, respectively; there were no statistically significant differences between the mean values). This should be interpreted as a lack of a dominant preference in this regard – somewhat surprisingly, the young people were equally likely to travel to the same locations as new ones. What is more, the respondents did not consider traveling to familiar places as overly boring (2.69). Curiosity about new destinations probably limits the tendency to return to those already visited, but with the mean value of 3.08, this is not a very strong sentiment. On the other hand, respondents recognized traveling to well-known places as somewhat less risky (3.09) but rather did not agree with the opinion that visiting a new place may be stressful (2.06) (see Table 3). Table 2. Mean, maximum, minimum, and median values for answers concerning recommendation intention and revisit intention Items Minimum Maximum Mean Standard deviation Median I return to visited destinations, but usually after a long time (a few years) 1 5 3.16 0.923 3.0 I mostly travel to the same destinations 1 5 2.18 0.797 2.0 I never return to destinations I have visited before 1 5 2.32 1.005 2.0 I am willing to share negative opinions about the destinations I visit 1 5 4.03 0.976 4.0 I am willing to share positive opinions about the destinations I visit 1 5 4.57 0.762 5.0 If I liked the destination, I encourage other people to visit it 1 5 4.54 0.786 5.0 Source: own elaboration. 1 – strongly disagree and 5 – strongly agree. Table 3. Mean, maximum, minimum, and median values for the answers concerning risk and uncertainty perception, novelty and variety seeking, and social bonding Items Minimum Maximum Mean Standard deviation Median If I were to visit the same destinations, it is because I am curious how theplace and people have changed 1 5 2.84 0.991 3.0 I return to a destination I have already visited to show it to other people 1 5 3.30 1.077 4.0 I return to the previously visited place for people who are living there (family,friends, acquaintances) 1 5 3.32 1.181 4.0 I like to spend my holidays in a familiar place 1 5 3.23 0.987 3.0 Traveling to the same places is less risky 1 5 3.09 1.092 3.0 Visiting new places is stressful 1 5 2.06 1.051 2.0 Traveling to destinations already visited is a waste of money 1 5 1.99 0.970 2.0 There are so many places to see that I do not have time to visit the same destinations again 1 5 3.08 1.216 3.0 Traveling to the same places is boring 1 5 2.69 1.140 3.0 Source: own elaboration. 1 – strongly disagree and 5 – strongly agree. 338 E. Wąsowicz-Zaborek The main statistical method for testing the research hypotheses was a structural model estimated by the partial least squares (PLS) method. According to the best practices outlined in the literature, the first step in investigating a partial PLS model is to establish the quality of the so-called measurement model, which defines relationships between latent constructs and their indicators. According to the procedures recommended by Hair et al. [2017], the metrics for average variance extracted (AVE) and composite reliability (CR) were calculated in order to verify the correctness of the investigated constructs (Table 4). For each factor, CR was greater than 0.7 and AVE exceeded the 0.5 threshold. These figures, combined with the absolute values of factor loadings exceeding 0.6, demonstrate the high reliability of all the extracted factors [Hair et al., 2017]. For further confirmation of the quality of the constructs, discriminant validity was investigated to check if sufficient differences exist between latent variables. Fornell and Larcker [1981] suggested that discriminant validity could be established when the square root of AVE for each construct is higher than the correlation coefficients between the focal construct and all the other constructs in the model (Table5). Since all the correlations are smaller than the square roots of AVEs, it can be concluded that all latent variables show appropriate separation from each other and there are no big overlaps in their meaning. To provide additional insights about the quality of the model, Stone–Geisser’s Q2 metrics were computed for the two endogenous constructs, using the blindfolding procedure with an omission distance of 7. Their respective values for RVI and RI were both positive and equal to 0.196 and 0.061, respectively, which point to predictive relevance of the structural model [Hair et al., 2016, p. 212]. Table 4. Indicators of construct variables in the study Indicators Sources of scale indicators Factor loadings Composite reliability Average variance extracted Risk and uncertainty perceptions (RUPs) 0.833 0.625 RUP 1. Visiting new places is stressful Boksberger and CraigSmith [2006]; Fuchs and Reichel [2008] 0.740 RUP 2. Traveling to the same places is less risky 0.748 RUP 3. I like to spend my holidays in a familiar place 0.877 Novelty and variety seeking (NVS) 0.858 0.669 NVS 1. Traveling to the same places is boring Lee and Crompton [1992]; Kim and Kim [2015] 0.811 NVS 2. There are so many places which I want to see that I do not have time to visit the same destinations again 0.853 NVS 3. I would prefer to spend my money for visiting new places than the already known 0.787 Social bonding (SB) 0.812 0.598 SB 1. I return to the previously visited place for people who are living there (family, friends, acquaintances) Jang et al. [2009]; Luoand Hsieh [2013]; Kyle et al. [2005] 0.653 SB 2. I return to a destination I have already visited to show it to other people 0.958 SB.3 If I were to visit the same destinations, it is because I am curious how the place and people have changed 0.653 Recommendation intention (RI) 0.864 0.684 RI 1. If I liked the destination, I encourage other people to visit it Alexandrov et al. [2013]; Chi and Qu [2008] 0.895 RI 2. I am willing to share positive opinions about the destinationsI visit 0.902 RI 3. I am willing to share negative opinions about the destinationsI visit 0.661 Revisit intention (RVI) 0.771 0.619 RVI 1. I never return to destinations I have visited before Luo and Hsieh [2013]; Kozak[2001]; Belloand Etzel[1985]; Chi and Qu [2008] −0.875 RVI 2. I mostly travel to the same destinations 0.802 RVI 3. I return to visited destinations, but usually after a long time (a few years) 0.670 Source: own elaboration. Antecedents of loyalty intentions among young adult tourists 345 Appendix Figure A1. Structural equation model for antecedences for destination loyalty intention among young adults. Diagram of regression paths between research constructs. Source: own elaboration.