Beyond the Sports Event: Assessing Season-Wide Effects on Winter Vacationists’ Destination Image

1 Introduction

Ski racing events in Alpine ski destinations are a special case for tourism marketing, as the sports event shows an activity which represents a major attraction factor for the destination’s visitors. Whenever an Alpine destination is faced with the decision to host an international competition in skiing or snowboarding, a common narrative brought up in the ensuing discourse is the ‘priceless advertising’ provided by the media coverage, which will surely boost the destination’s image worldwide and thus attract visitors to the destination. A review of news media and ski destination websites shows that this claim has been made by political office bearers and representatives of tourism all over the Alps and beyond, such as Andorra’s head of government (Andorra2029, 2021), the governors of South Tyrol (Saslong, 2017) and Styria (World Cup Magazine, 2019), the mayor of Flachau (MeinBezirk, 2021), the canton council of Bern (HTR, 2020), the deputy economy minister of Georgia (Agenda, 2024) the tourism ministers of Bulgaria (Bulgarian Ministry of Tourism, 2022), Quebéc (Tremblant World Cup, 2023) and Alberta (Canadian Press, 2024), the tourism state councilors of Styria (Reiteralm.at, 2021) and Carinthia (Land Kärnten, 2017), and the tourism chairman of Vienna (ORF, 2015).

The expected mechanism of action behind this effect has received little critical examination: The audience following Ski events on the media are most likely active skiers looking to book a ski holiday and now that they have been made aware of this specific destination and its qualities, they are likely to become future guests soon. However, this logic does not consider that the viewing audience might follow further events organized in other destinations and that the choice of a winter holiday destination encompasses much more than just winter sports (Bausch & Gartner, 2020). In their literature review about destination choice, satisfaction and loyalty of ski tourists Ul Islam et al. (2023) discuss 15 publications covering ski resorts all over the world. Not one of these publications mentions events as a ski destination choice criterion. A further review of publications about the impact of sports events between 2010 and 2022 (Zourgani & Ait-Bihi, 2023) revealed that the focus of research in that field was mainly on their direct, especially economic and social effects.

Even though destination image effects of large scale and mega-events partially have been discussed (for example, Kim, 2014; Lai, 2018), these studies were about one-off events and their effects on visiting or revisiting intentions (Gibson et al., 2008) or media coverage (Preuss & Alfs, 2011). Furthermore, studies focusing on participants of sport events and the effects of their participation on the destination image can be found. Newland and Yoo (2021) analyzed effects to attract active sports tourists for future participation. In this context, a meta study by Z. Chen et al. (2023) found a positive correlation between the event quality perceived by participants and spectators and their destination image.

The effects of yearly held international sport events as a part of a World Cup series on the destination image besides the events itself have not been addressed in research up to now. So far, there is no empirical evidence to show if an annually recurring sports event that lasts only one or a few days influences tourists’ destination image and their intentions over the whole season. To close this gap our study examines the effect of an annually held international winter sports event which is part of the World Cup races series of the International Ski and Snowboard Federation (FIS, 2024). These events take place with broad media coverage, especially by the national TV channels in the destination’s source markets.

The research question of the study is: How do the FIS Ski World Cup races in Alta Badia affect the perception and behavioral intentions of tourists visiting during the regular ski season, outside of the event period?

We will analyze the effects of the event by applying the well-established destination content model (DCM) developed by Kock et al. (2016). By using this conceptual framework as pictured in figure 1, we measure the effect the event has on the tourists’ perceptions and evaluations of the destination, which in turn influence their behavioral intentions.

Figure 1:

Conceptual analysis framework based on DCM of Kock et al. (2016)

Additionally, an analysis of the answers to an open-ended question examines the visitors’ personal perceptions of this effect. This additional qualitative element of the study supplements and confirms the quantitative results by further qualitative insights.

Based on this approach, this study is the first to conceptualize the potential impact of an annually organized international two-day winter sports event that is widely reported in the media on the all-season image of the hosting destination. It analyzes these effects and derives implications for destination marketers’ communication strategies. The study contributes to the development of theory by applying the destination content model to a different type of destination and a more specific research question that has not yet been sufficiently explored in tourism research. As the underlying research gap is based on a widespread assumption in winter sports tourism, the study also provides a practical contribution to the field of tourism marketing.

2 Sport Events and Destination Image – a Literature Review

While very specific definitions of the terms “event” and “destination image” are used in the empirical part of this study - i. e. recurring ski race events in winter sports destinations and the definition according to the destination content model (Kock et al., 2016) - these terms are used more broadly for the purposes of the literature review. Both sports events and destination image are two large fields of research, and this review focuses strictly on publications addressing their interaction - the effects of sports events on destination image. Generally, the effect is assumed to be of a positive nature: In 1984 Brent Ritchie stated “The sponsoring of many hallmark events has often been based on the assumption that the event leads to the enhancement of the awareness and reputation of the host region from both a tourism and commercial standpoint”. More specifically, Getz (2008) argued in his review about event tourism that one of the main reasons for a destination to host and promote an event is “to foster a positive destination image and contribute to general place marketing”. Especially for televised sport events, the hope is to attract viewers and event visitors to the destination for a holiday independently of the event itself (Gibson, 1998).

Previous research has identified several factors influencing the effect of a sport event on destination image: One basic condition for a positive image transfer between the event and the destination is that the event is perceived positively by potential visitors and is not overshadowed by negative perceptions, for example through media reports about controversies, protests or crime (Preuss & Alfs, 2011; Schroeder & Pennington-Gray, 2014; Swart et al., 2018). Another important prerequisite is that the event and destination are a good match. This concerns the ‘image fit’ in the perception of the visitors (Hallmann & Breuer, 2010a), as well as the cultural and strategic fit from the perspective of the destination stakeholders (Jago et al., 2003). Accordingly, the effects have been found to vary between different types of events (Y. Kim et al., 2019), and also for the same event in different national source markets (Heere et al., 2019; S. S. Kim & Morrsion, 2005). The strength of the effect also seems to be connected to the level of involvement in the event. Some studies have found differences between regular visitors of the destination during the time of the event and event visitors (N. Chen & Funk, 2010; C.-K. Lee et al., 2005), as well as between passive event visitors and active event participants (Hallmann et al., 2010; Hallmann & Breuer, 2011). However, a study by Kaplanidou (2006) found no such differences. It has also been shown that the effect decays over time, both for one-time (Ritchie & Smith, 1991) and recurring events (King et al., 2015).

However, the effect of recurring ski race events on the image tourists have of an Alpine ski destinations can only be conjectured so far. A study relatively close in context is a qualitative ex-post asessment by Kaiser et al. (2013) on stakeholders’ views of the 1999 Nordic Ski World Championships in the destination Ramsau am Dachstein, and the 2001 Alpine Ski World Championship in the destination St. Anton am Arlberg. Both cases were one-time events which were broadcast on national television in the relevant source markets and - at least in the case of St. Anton, concern a classic Alpine ski destination. For these cases, the stakeholders perceived that the events did not have the initially expected effect of attracting new visitors from previously untapped market segments.

There are a few publications examining the effect of recurring sport events on the destination image of the respective host community. However, the sport events examined in these publications are smaller and do not receive broad and international media attention. Marathon or triathlon races (An & Yamashita, 2024; Hallmann et al., 2010; Hallmann & Breuer, 2010b, 2010a; Jeong & Kim, 2020; Kaplanidou et al., 2012), and kart or bicycle races (Chalip et al., 2003; Kaplanidou & Vogt, 2007) might attract a considerable amount of viewers and participants but they are not comparable to a mass market as skiing, where one of the tourists’ main travel motives is to practice this sport during their vacation (Cala, 2024). Therefore, the transferability of these studies to alpine skiing and World Cup ski races is severely limited.

Looking at the relationship of sport events and destination image in a broader context, extensive tourism research has focused on the effects of one-time mega-events such as Olympic Games (Hahm et al. 2019; Lai, 2015, 2018; Ritchie & Smith, 1991) or World/European Championships in Soccer (e. g. Andersson et al., 2021;S. Kim & Morrsion, 2005; Rojas-Méndez et al., 2019) and Athletics (N. Chen & Funk, 2010; Jin et al., 2013; Y. Kim et al., 2019). For these studies, the examined destination is typically either the host country or host city.

The findings of these previous studies vary strongly, dependent on the study design and choice of sample. Studies surveying on-site tourists during the event (Kaplanidou, 2006; Lai, 2018), event visitors (Andersson et al., 2021; Florek et al., 2008; Hallmann & Breuer, 2011; Jeong & Kim, 2020, 2022; Jin et al., 2013; Sung Moon et al., 2011) or active participants (An & Yamashita, 2024; Hallmann & Breuer, 2010a, 2010b; Kaplanidou & Vogt, 2007; King et al., 2015), predominantly find positive effects on destination image with only very few exceptions (P. Lee et al., 2022; Swart et al., 2018). Some studies also suggested that cognitive image attributes can be transferred from the event to the destination (Kaplanidou et al., 2012; Lai, 2015), or that a sport event creates a perception of a more active destination (Xing & Chalip, 2006). However, studies taking a more removed approach, such as surveying random samples in tourism source markets (Bodet & Lacassagne, 2012; Chalip et al., 2003; Hahm et al., 2019; Heslop et al., 2010; Li & Kaplanidou, 2013; Liu et al., 2021; Rocha & Fink, 2017; Rojas-Méndez et al., 2019) or monitoring international media reports (Preuss & Alfs, 2011) and posts on social media (Banyai & Potwarka, 2012) frequently found mixed effects including some negative changes, or no effect at all.

Overall, the widely claimed positive image effects beyond the event itself have not been backed by scientific evidence. Looking at the season duration of ski resorts a further problem must be pointed out: the skiing season in most of the leading Alpine ski resorts starts at the end of November and lasts until mid-April (Steiger et al., 2023). The event itself takes place for two to four days within this skiing period of 100 to 120 days (FIS, 2024). And while the event might be perceived as singular and unique from the perspective of the destination, it is one amongst many weekly presented ski events in the media, showing competing destinations. Thus, this study provides a first scientific investigation whether such a yearly held ski sport event has a significant effect on the relevant target group – the ‘regular’ ski vacation guests, most of them visiting the destination outside of the event period.

3 Measuring the Effects of an Event Using the Destination Content Model

The argument that major sporting events represent a great value for the destination as a competitive unit in tourism requires further specification. In destination image literature a frequently analyzed aspect is linked to the tourists’ intended behavior. The relationship of the destination image, its cognitive, affective and conative components (Tasci & Gartner, 2007) with tourists’ behavioral intentions has been comprehensively analyzed on the basis of psychological approaches (Afshardoost & Eshaghi, 2020). This research revealed three main effects which can unfold a positive effect on the long-term destination development by the tourists: (1) willingness to visit (Assaker et al., 2011; Papadimitriou et al., 2015), (2) sharing their positive impressions of the destination by word of mouth (Prayag et al., 2017; Stylidis et al., 2017), and (3) willingness to pay (Kim et al., 2022; Kock et al., 2016). Thereby, the willingness to visit has two time-dimensions: to attract first-time visitors (Molinillo et al., 2018) and to create a higher revisiting rate by current visitors (Loi et al., 2017).

Kock et al. (2016) developed the Destination Content Model (DCM), which provides a comprehensive theoretical framework outlining the different image components, their interrelations, and their influence on behavioral intentions. The model distinguishes between the multitude of individuals’ associations with the destination–referred to as Destination Imagery (DY)–the tourists’ experienced affect towards the destination (DA), and a heuristic overall evaluation called Destination Image (DI).

In the model, DY is defined by Kock et al. as “an individual’s diverse cognitive and affective associations relating to a destination”. After further detailed discussion the authors conclude for the model: “as such, while DY includes affective descriptors, the construct is cognitive in nature”. DY is strongly linked to the destination type, and when operationalizing the model, the items for DY must be tailored to the key characteristics and features of the destination. While an individual’s DA may vary between destinations, the construct used to measure DA is independent of the destination type. A prominent approach to measuring DA was developed by Russell et al. (1981), based on four bipolar emotional axes. In the DCM, DY represents the individual descriptive input characterizing a person’s perception of the destination, whereas DI serves as the evaluative output, reflecting an overall judgment. This judgment is based on both DY and DA. The segmentation into these three core components aligns with the conceptual framework of Tasci and Gartner (2007), which encompasses cognitive (DY) and affective image attributes (DA), as well as an overall image (DI).

Finally, the model integrates three outcome variables related to tourists’ behavioral intentions: willingness to visit (WTV), word of mouth (WOM), and willingness to pay (WTP). The DCM is grounded on five hypotheses:

H1: Destination Image (DI) has a positive effect on tourist behavior. Specifically, destination image positively relates to (a) willingness-to-visit (WTV), (b) willingness to provide word-of-mouth recommendations (WOM), and (c) willingness-to-pay (WTP).

H2: Destination Imagery positively relates to Destination Image.

H3: Destination Imagery positively relates to Destination Affect.

H4: Destination Affect positively relates to Destination Image.

H5: Destination Affect has a positive effect on tourist behavior. Specifically, Destination Affect positively relates to a) willingness-to-visit, b) word-of-mouth, and c) willingness-to-pay.

For the purpose of our study, we apply these five hypotheses directly from the original model to the case of an Alpine skiing destination. Following the directionality of the model, we add three further hypotheses of the event’s effects: H_E1 to H_E3. First, that the event can have a direct effect on the destination imagery DY. This was shown by Sagheim and Aas (2019) analyzing two endurance sport events in Scandinavia for organizational issues, scenery or landscape. This effect can be caused by taking part in the event, following the event in the media or getting aware of the event and related activities and facilities.

H_E1: The yearly repeated sports event has a positive effect on destination imagery

Also, in the study of Sagheim and Aas (2019) and a further study of Moghaddam et al. (2024) the emotional effect of winter sport events was shown. Attending such a sport event in person or even a media-based participation has a direct emotional outcome as excitement, fulfillment or joy. We therefore hypothesize second, that the sport event has a positive impact on the destination affect:

H_E2: The yearly repeated sports event has a positive effect on destination affect

The link between the overall evaluation of the destination image and the destination brand equity had been discussed by Konecnik and Gartner (2007) based on destination awareness, image, quality and loyalty. This approach was refined and confirmed by Ekinci et al. (2023) proposing a model with seven factors: brand awareness, physical quality, service interaction quality, brand self-congruence, brand identification, destination brand trust, and destination brand loyalty. At least for brand awareness we can hypothesize that visiting on site or a following of the event in the media will increase awareness. This allows the third assumption that there is also a positive impact to the overall evaluation of the DI as a measure linked with the brand equity.

H_E3: The yearly repeated sports event has a positive effect on the overall evaluation of the destination image.

Following previous research on events and destination image, the event was operationalized in two ways. The first measure adapts the concept of image fit (Hallmann & Breuer, 2010a) to represent the individual’s perceived compatibility of the event with the destination (EC). The second measure captures how the individual perceives the influence of the event on the attractiveness of the tourism destination (EA), which represents an adaption of perceived value as defined by Zeithaml (1988), which has been used in similar contexts by previous research (Jeong & Kim, 2020; Jin et al., 2013). The extended conceptual model is represented in Figure 2.

Figure 2:

Conceptual model, based on Destination Content Model (Kock et al., 2016)

4 Materials and Methods

5 Results

First, we analyzed the frequency distribution of the manifest variables used in the model (see Table 3). The knowledge about the event (EK) and the communication about Alta Badia after the stay (WOM) showed a distribution among all scale values. This is not astonishing, as most Alpine ski resorts have a high share of repeat visitors. In this study only 11.6 % of the participants were first-time visitors and 60.3 % of all visitors had already been to Alta Badia more than 5 times. Therefore, high positive values for the overall satisfaction and the positive poles of the affective variables show the content validity of the data.

As structured equation models react sensitively to multicollinearity (Streukens & Leroi-Werelds, 2023), we calculated the variance inflation factors for the variable blocks used for the DY1, DY2 and DA (see Table 4). All three blocks did not show any indications for multicollinearity, as the VIF values were clearly below the commonly used threshold of 5. None of the variables needed to be excluded from further analysis.

First the quality of the measurement model for the latent variables was assessed through confirmatory factor analysis. The CFI was 0.962, which is above the recommended threshold of 0.95. This indicates a good fit between the data and the model. Also, the value of the Tucker-Lewis Index of 0.937 was near to the acceptable cutoff of 0.95, suggesting a reasonably good fit. Finally, the RSMEA with 0.071 and standardized Root Mean Square Residual (SRMR) with a value of 0.046, were near to or well below the cutoff of 0.08, indicating an acceptable or good model fit (all threshold values taken from Hair et al. (2013)). Furthermore, we did a Harman’s single-factor test showing a poor fit (CFI = 0.806, Tucker-Lewis Index 0.727, Root Mean Square Error of Approximation RMSEA = 0.136), indicating an absence of issues with common-method bias.

The summary of fit results for the SEM provided by lavaan indicated a good to very good fit in all quality of fit criteria: the Comparative Fit Index (CFI) with 0.940 was clearly above 0.9 (Fan et al., 1999), the Tucker-Lewis Index (TLI) with 0.909 above the threshold proposed by Byrne (1994), the RMSEA with 0.077 below the 0.08 used as threshold for larger samples (Hair et al., 2013) and finally the Standardized Root Mean Square Residual SRMR of 0.045. In total the model fit can be supposed to be good to very good. Table 5 shows the results of the estimation of the standardized model coefficients and related significances. In this table rhs is indicating the independent and lhs the dependent variable (in the graph of Figure 2 symbolized by an arrow) of the regressions in the model.

These results can be transferred to figure 3 showing the effects by a path model.

Figure 3:

Path model results for the event factor expanded destination content model (DCM)

In our model we confirm H3, the impact of destination imagery DY on the destination affect DA (0.562***), but not from DY to the overall evaluation of the destination image DI (H2, -0.083). Furthermore, we also found a strong significant influence of DA on the tourists’ future intentions concerning the willingness to pay WTP (H5a, 0.540***), their word of mouth communication WOM (H5b, 0.219**) and the intention of revisiting WTV (H5c, 0.634***). We were unable to confirm the influence of DI on these three behavioral intentions (H1a, WTP 0.094, H1b, WOM 0.136 and H1c WTV 0.071). Concerning the impact of the event EV as additional push factor on DY, DA and DI we found only for two of the three a significant positive impact. The higher value of the standardized coefficient of 0.497*** for EV -> DY (H_E1) indicates a stronger impact on destination imagery than the 0.219*** for EV -> DA (H_E2) on destination affect. A significant impact of EV on DI (H_E3) with a standardized coefficient of -0.094 could not be confirmed. Figure 3 shows the results represented as path model.

To complete the quantitative results the texts from the open ended question about the event’s effect on the destination image were inductively coded and analyzed (Braun & Clarke, 2006). Four main themes were identified (see also table 6, anchor quotes, original text translated to English). The most prevalent theme is overall quality and competence of the ski resort. The participants perceive that the construction and maintenance quality of the slopes and lifts, and consequently the overall skiing quality is positively influenced by the World Cup races. The second one is the possibility to ski on the World Cup slope. While the answers very rarely focus on the appreciation of the slope’s technical intricacies, it has a high experience value to “follow in the tracks of the world’s best skiers”. Thirdly, the participants feel that the destination gains in prestige and recognition value through the event, which “attracts a certain target group”. And lastly, the destination profits from the spectacle and the atmosphere of the event and the surrounding festivities.

The few negative perceptions revolve around the inconvenience for regular ski tourists during the time of the event such as crowding, closed slopes, and booked out rooms.

6 Discussion

This study analyzes the role of an annually held international sports event with broad media coverage on the perception of a destination and the tourists’ intentions linked to the destination. As basis for the proposed model, we used the destination content model (DCM) developed by Kock et al. (2016). We applied and extended this model consisting of destination imagery, destination affect, destination image and tourists’ intentions by adding the effect of the event as a potential push factor. The study examined the case of Alta Badia, a mature, highly developed winter vacation destination in Italy with two annual FIS men’s World Cup races.

The surveyed ‘regular’ ski and winter vacationists mostly confirmed a good fit between the event and the destination’s image, and partially perceived that the event increases the attractiveness of the destination. However, the event did not show a significant positive impact on the destination image, measured by the overall evaluation of the destination. The overall evaluation is very positive with little variation, which is also reflected in the high proportion of repeat visitors. Therefore, we assume that repeat visitors already have developed a stable and very positive overall evaluation of the destination image independently of the event, which in most cases does not take part during their stay.

The event showed significant (α<0.01) direct effects on both destination imagery and destination affect. Destination imagery represents in our case their association and valence of attributes of a winter and ski destination. Examining the estimated standardized coefficients, the effect on the destination imagery is even stronger than for destination affect. This result corresponds with the qualitative analysis of the statements respondents made to describe how the event makes the destination more, or less attractive to them personally. The vacationists perceived several positive effects beyond the period of the event itself, including specific skiing attributes related to the destination imagery, and intangible qualities of the destination connected to destination affect. The overall picture shows a dominance of cognitive elements of the touristic product skiing, which is the core of a winter holiday stay to most guests. The affective attributes can be found as well, but they are clearly in second line and linked to experiences and the atmosphere.

Following the path in the model the influence of destination affect (DA) on the overall evaluation of the destination image shows the highest value among all estimated standardized model coefficients. Thus, even though the event does not contribute directly to the positive overall evaluation it takes the role of a booster via the affective dimension of the destination content model. Notably, this positive boost of the destination affect is also transferred to the behavioral intentions, indicating that the event contributes positively to the guests’ willingness to visit (WTV) and recommend the destination (WOM), and to pay a premium price (WTP). While the model does not explicitly measure the direct impact on WTV, WOM, and WTP, the increased values in DA due to the event will contribute to all these effects.

Finally, the results indicate that there is no significant influence of the overall evaluation of the destination image (DI) on these three behavioral intentions. As already mentioned, this is probably caused by the high share of repeat visitors and thereby a generally high guest satisfaction. Statistically this leads to a relatively low variance of DI within the model. Therefore, neither the direct path of the event nor the indirect by the destination affect through DI can influence the three components of intended behavior.

Finally, our text analysis of the open-ended question complements the findings of previous research on the dynamic of the image transfer between the event and the destination on a content level: Kaplanidou et al. (2012) found that for active event participants of a recurring marathon race, the destination image contains certain characteristics of the event. Even though this study has a different context, a similar dynamic is found for a small part of the sample, represented in the theme spectacle. However, the World Cup races do not let the destination appear more active as was found by Xing & Chalip (2006) but rather serve as a hallmark of quality and recognition. This helps to position the destination as a premium product but does not necessarily make it more attractive for a sportive audience primarily focused on technical skiing. This could explain why the study of Kaiser et al. (2013) found that Alpine destinations were disappointed in an event’s ability to attract new target groups.

7 Conclusions

8 Limitations

This study used a convenience sampling method with the known limitations about representativeness. Comparing the socio-demographic sample structure (see table 2) with official statistics it fits well, but this is not a guarantee against bias. Using Likert Scales for most manifest variables (Dolnicar and Grün, 2013) the known limitations of this scale type in cross-cultural studies have to be recognized. The survey of our study was done over a period of four weeks from mid of February to mid of March. Even though this long period allowed to reach guest from the key source markets, we did not cover the period of the event itself, which always takes place in December. Thus, not having had a further survey in December we were not able to compare the direct effect of the event on guests staying in the destination during the event and especially for those having visited it, and the indirect effect for the main part of guests having had their vacation after the event. Moreover, the study focused on a very specific setting of event, destination and guest profile, which limits the transferability of the findings and practical implications to other cases. Therefore, for other annually organized events held at destinations of clearly other type as e. g. large cities or coastal regions and of other event character e. g. culture or food fairs besides the event itself other potential push factors might need consideration in the model.