Active sport event participants’ behavioural intentions: Leveraging outcomes for future attendance and visitation

Abstract

A key concern for event organisers and community leaders is how events can be leveraged for repeat visitation to the destination and event. This study investigated how sport event and destination attributes influence behavioural intentions of active sport tourists and further discussed how this knowledge can be leveraged by the sport event and destination marketers to attain positive business outcomes, namely repeat event participation, repeat destination visitation, and positive word of mouth. A survey of 649 active sport event participants was conducted. The analysis revealed that event and destination attributes had both direct and indirect effects on behavioural intentions of active sport tourists. Implications for leveraging behaviour outcomes for future attendance and visitation are discussed.

Keywords

Active sport events active sport tourism behavioural intention cross-leverage destination marketing leverage

Introduction

Over the last 20 years, the active sport tourism sector – where athletes travel to actively participate in sport events as part of their vacation (Gibson, 1998) – has grown to such a level that there is an increasing concern by destination marketers, governmental tourism agencies, and politicians to focus on how sport events can be leveraged to promote tourism (Aicher and Newland, 2018; Getz, 2008; Kim and Chalip, 2010; Taks et al., 2009; Ziakas and Costa, 2011). While much of the focus has been on large-scale, spectator events, (e.g., Kirby et al., 2018; Schulenkorf et al., 2016; Taks et al., 2009), there has been a shift to consider the impacts of active sport tourism (Funk et al., 2007; Kaplanidou and Gibson, 2010; Newland and Aicher, 2018) and the tourism potential of smaller scale events (Daniels and Norman, 2003; Kaplanidou and Gibson, 2010) and rural events (Costa and Chalip, 2005; Newland and Robertson, 2018; Robertson et al., 2014).

Much of the research to date has focused on how destinations use sport events to build a destination brand (e.g., Chalip and Costa, 2005; Robertson et al., 2014), how destination image influences repeat visitation (e.g., Kaplanidou and Vogt, 2010), how destination image changes following the event (e.g., King et al., 2015), and how an event portfolio is used as a development tool for the destination (e.g., Ziakas, 2014; Ziakas and Costa, 2011). Likewise, on the sport event side, much work has been done to explore how the event can capitalise on the destination location (Kaplanidou, 2010), sport involvement and tourism (Chang and Gibson, 2011; Funk et al., 2007), motivation to participate in sport events (Aicher et al., 2015; Cassidy and Pegg, 2008; Getz and McConnell, 2011; Kaplanidou and Gibson, 2010; Kurtzman and Zauhar, 2005; Newland and Aicher, 2018), travel conditions and the influence of social worlds (Aicher et al., 2020; Buning and Gibson, 2016a, 2016b), how sport tourists segment by sport (e.g., running, triathlon, cycling) and athlete type (novice to elite; Aicher and Newland, 2018), and the perceptions of rural sport event tourism (Newland and Robertson, 2018).

While the literature has begun to provide a good picture of what destination elements drive repeat visitation, and what sport event factors motivate attendance, what is missing is the discussion on how this information can be leveraged for repeat visitation to the destination and event. Event leveraging focuses on strategic processes that can be applied across event and destination contexts (Chalip, 2018). Sport event tourists stay at a destination for a brief window of time, so it is important for the destination to optimise the value of the event attendee by finding opportunities to lengthen stay, entice spend, and strengthen business relationships that enable collaboration, and retain expenditures in the community (Chalip, 2018; Chalip and Leyns, 2002; O’Brien, 2007). It is critical that destinations develop event portfolios that enable cross-leveraging of events in order to develop a sustainable tourism strategy by integrating the sport event into the entire service mix of the destination (Ziakas, 2014, 2019). While it is important to implement leverage opportunities during the event, it is also vital to find ways to induce repeat travel to the sport event and/or destination as well as stimulate word of mouth (WOM) activity that inspires this behaviour in others (Murphy et al., 2007; Newland et al., 2018; O’Brien, 2007; Taks et al., 2009). As Newland et al. (2018) found that the more satisfied an athlete is with an event, the more likely they are to tell others and Murphy et al. (2007) observed that travellers are more likely to rely on other travellers for WOM about the destination. Therefore, this study seeks to explore how the sport event and destination influence repeat visitation to the destination for leisure, whether the athlete will return to the same destination to participate event again, the likelihood the athlete will tell others about the event and/or destination, and how this knowledge can be leveraged by event owners and cross-leveraged by the destination. With this knowledge, event and destination operators can enhance their understanding of how attributes influence behaviour and how that can be leveraged for future participation and tourism.

Literature review

Event characteristics and event/destination behavioural intentions

The event can enhance its brand by capitalising on a favourable destination (Kaplanidou, 2010), but it seems that for some active sport participants, the event factors play a bigger role than the destination attributes (Newland and Aicher, 2018). In order to capitalise on sport tourism’s growth and begin to offer better explanations as to why individuals select and return to certain events, researchers have called for a stronger understanding of sport tourists’ behaviour (Aicher and Newland, 2018; Hemmatinezhad et al., 2010). The recent work on sport event participation has focused on the intrinsic and extrinsic motives that drive participation (Aicher et al., 2015; Funk et al., 2007; Newland and Aicher, 2018). This work is derived from Crompton’s (1979) tourism motivation framework, which identifies the factors that push (intrinsic drivers) versus pull (extrinsic drivers) a sport event tourist to the destination or event (Baloglu and Uysal, 1996; Caber and Albayrak, 2016; Crompton and McKay, 1997; Dann, 1977; Newland and Aicher, 2018). There are a number of reasons that drive athletes to choose and travel to a sport event. These event attributes can include the challenge of the course, course scenery, the reputation of the event, cost, accessibility, travel companions, the competitiveness of the field, personal endeavours, among others (Aicher and Newland, 2018; Buning and Gibson, 2016a, 2016b; Lough et al., 2016). Those same athletes might be driven to the destination because of the event specifically or because they are seeking a place to explore or escape to after the event. What is critical for sport event managers and destination marketers to understand is how the destination and/or event attributes interact to influence sport event participant behaviour after they have completed the event (Aicher et al., 2020; Kaplanidou and Gibson, 2010; Taks et al., 2009) Especially given that event attributes have been shown to have a direct effect on event loyalty (Yoo et al., 2020).

Research suggests there are a number of key elements that can impact event attendance and repeat visitation, like event image, event characteristics, athlete characteristics, word of mouth (WOM), personal resources, and travel conditions. Kaplanidou (2010) found that the sport event image is considered to be critical for increasing attendance to active sport events. According to Kaplanidou, sport event image is defined as, ‘cognitive and affective perceptions related to emotional, organizational, environmental, physical, and social aspects that are permeated by common and unique attributes’ (p. 383). A further study also observed that event characteristics predicted destination repeat visitation and participation in the event and WOM about the event (Kaplanidou et al., 2012). While this is important, it is noteworthy that several researchers found that athletes more immersed or highly identified with their sport are less likely to return to an event, even if they are satisfied (Aicher et al., 2018; Buning et al., 2017). Novelty, or continually seeking a new event experience, appears to be important to athletes highly involved in the sport. There are factors that could influence event-related behaviour, such as personal resources or travel conditions. Personal resources, like the amount of time, money and/or accommodation, can positively influence the level of event loyalty (Yoo et al., 2020). Buning and Gibson (2016b) showed that active sport participants found travel preferences vary with travel conditions and that destination attractions become much more important when travelling with non-sport companions or over longer distances. Travel conditions explain the conditions surrounding the trip that impact behaviour, such as travelling with family or other athletes (Aicher et al., 2020; Buning and Gibson, 2016b). What could be critical for the event managers is the importance of WOM between athletes, especially if they are satisfied with the event (Newland et al., 2018). O’Brien (2007) argued that WOM ‘played the key promotional role, where past participants communicated the dates and details [of the event]’ (p. 154). Likewise, Getz and McConnell (2011) noted how the importance of WOM advertising within the cycling community is vital to event organisers.

This study sought to better understand how behavioural intentions are influenced by the presence of preferred event attributes. These sport event attributes included the reputation/prestige, longevity/ history, challenge of the course, event cost, quality of the expo, registration merchandise, course scenery, level of competition in the field, and value of the experience for the cost (Buning and Gibson, 2016a; Newland and Aicher, 2018). Therefore, the following hypotheses were considered based on event attributes:

H1: Event attributes are positively associated with event behavioural intentions (i.e., repeat participation and positive WOM about the event).

H2: Event attributes are positively associated with destination behavioural intentions (i.e., revisit for other leisure activities and positive WOM about the destination).

Destination attributes and event/destination behavioural intentions

The importance of destination image in predicting intentions to revisit has been discussed in the sport tourism literature (e.g., Kaplanidou, 2010; Kaplanidou and Gibson, 2010; Kaplanidou et al., 2012; King et al., 2015). Destination marketers have used sport as a means to enhance the image of the destination in order to amplify the host’s attraction as a tourism destination before and after the event (Chalip, 2004). Sport events also provide economic impacts (Chalip, 2018; Chalip and Leyns, 2002), media attention (Chalip et al., 2003), social impacts (Chalip, 2006, 2018), and tourism impacts (Getz, 2008) that can also serve to enhance or rectify the destination’s image (Chalip and Costa, 2005; Kaplanidou and Vogt, 2007).

Whether an event participant decides to return to a destination to compete again or for tourism activities is of importance to event and destination operators. Funk et al. (2007) found that athletes’ favourable perception of the destination did aid in decisions to visit a destination for a running event. However, the authors did not detail whether this would impact repeat visitation for other leisure activity nor repeat event participation. Building on this, Kaplanidou and Gibson (2010), showed that destination image influences attitudes towards event participation for recurring sport events. Kaplanidou and Vogt (2007) observed that while the destination image did not impact the sport event image, the destination did have an impact on the intention to return to participate in sport activities. One assumption often held by sport event owners and community leaders is that sport events can increase tourism after the event through repeat visitation. Kaplanidou et al. (2012) explored this and found that the destination atmosphere can influence repeat participation and WOM about the destination and event and the destination attractions influenced repeat visitation for leisure and WOM for leisure activities. On the contrary, Taks et al. (2009) found that Pan American junior athletes were less likely to participate in tourism activities and were unlikely to revisit the destination. Further, Buning et al. (2018) found that runners who were more immersed in their sport were less likely to revisit the destination. However, recent work by Yoo et al. (2020) found that event loyalty enhances destination loyalty. The authors argue that it is possible to capture repeat business if operators can find ways to use the sport event along with the greater event portfolio of the host destination to enhance loyalty (Ziakas and Costa, 2010)

This study sought to better understand how behavioural intentions are influenced by the presence of preferred destination attributes. These destination attributes included shopping, the nightlife (i.e., pubs and restaurants), family-friendly entertainment, guided tours, cultural, historical, and art attractions, safety, and chance of experiencing different culture (Aicher and Newland, 2018; Newland and Aicher, 2018). The following hypotheses were considered based on destination attributes:

H3: Destination attributes are positively associated with event behavioural intentions (i.e., repeat participation and positive WOM about the event).

H4: Destination attributes are positively associated with destination behavioural intentions (revisit for other leisure activities and positive WOM about the destination).

Leveraging the event and destination to influence behavioural intentions

Leveraging an event or destination refers to the employment of key tactics by stakeholders to maximise the benefits of an event (Chalip and Leyns, 2002). Immediate leveraging are tactics designed to maximise visitor spend and build new markets, where longer term leveraging uses an event portfolio to build the destination’s image (Chalip, 2004; O’Brien, 2007; Ziakas and Costa, 2011). A vital goal of destination marketers is to lengthen the stay of the visitor and entice further spending. Sport events are alluring to the destination because they attract new tourist money to the location. However, as noted above, researchers have suggested that many athletes are mainly interested in the sport event and the destination is secondary (Newland and Aicher, 2018). Also, many do not return to the event once the challenge has been accomplished. Therefore, the destination’s businesses must actively leverage the opportunity of the sport event in order to reap any benefit (O’Brien, 2007). As an example, Chalip and Leyns (2002) found that many business managers did not leverage opportunities to attract customers during the Gold Coast IndyCar race. In fact, many businesses were harmed by the event because not only did they fail to capitalise on the event tourists, their regular customers were deterred from the area by large event crowds and activities. While the crowds an event attracts can have negative outcomes, if businesses plan and implement tactics to exploit the masses, they can benefit significantly. This was apparent at the Noosa Festival of Surfing, where local businesses, like banks and liquor stores, implemented a number of tactics to tie into the event and attract tourists (O’Brien, 2007).

Knowing more about the event attendee can lead to improved leveraging of the event and/or destination. For example, Kaplanidou and Gibson (2010) found that satisfaction is a driving variable of positive behavioural intentions to participate in the event again, while the destination plays a complementary role. It is important to note that past participation does not guarantee future participation (Buning and Gibson, 2016b; Kaplanidou and Gibson, 2010). Therefore, event and destination marketers must explore the drivers of repeat visitation. One way this could occur is by considering how the sport subculture and/or the individual’s identity or immersion in the sport can influence the event goer’s experience and behaviour intentions (Buning and Gibson, 2016b; Green, 2001). Green (2001) highlights the importance of leveraging the event attendees’ identification with the subculture of the sport and suggests that in by doing so, sport events can be designed to broaden their appeal, and by extension repeat attendance.

Cross-leveraging the destination’s events

The relationship between key destination and event stakeholders is changing as city leaders push to maximise the benefits of events, including sport (Chalip, 2018; Ziakas, 2019). Cross-leveraging – or integrating other events in the destination’s portfolio to enhance flow on or future tourism – can help destinations to enhance their tourism offerings, build an image, and mitigate the impact of seasonality in order to help achieve sustainable tourism to the area (Ziakas, 2014). In other words, event managers and destination marketers must collaborate to find complementary offerings to serve multiple purposes in order to drive travel behaviour and obtain a variety of event benefits (Ziakas, 2019). While many destinations have grown wise to the importance of developing an integrated event policy the results are varied and inconsistent (Ziakas, 2019). In order to ensure that event goers will return to the destination for future leisure activity, the destination must strategically integrate and promotes its other offerings during the sport event (Chalip, 2018; Chalip and McGuirty, 2004; Newland and Aicher, 2018; O’Brien, 2007) as well as its other event offerings (Ziakas, 2014, 2019).

To be effective in the cross-leveraging process, the destination marketer must understand the sport tourists’ preferences in order to attract them to other destination events or tourism assets. For example, to build on differences between athlete preferences for the destination, Aicher and Newland (2018) found that runners, triathletes, and cyclists segment differently by athlete type, which can have a profound effect on their behaviour towards the destination. For example, runners were more likely to want to explore the destination, with interests in guided tours, entertainment offerings, and the nightlife. The triathletes were more likely to classify as escapists, interested in the environment and unguided sightseeing. On the contrary, cyclists just want to complete the race and go home. There was little interest in what the destination had to offer (Aicher and Newland, 2018). This is further supported by Chalip and McGuirty (2004), who suggested that bundling features of the event with key, subculture-specific attractions could appeal to event attendees and extend their stay. Finally, Yoo et al. (2020) observed that personal resources, like time and money, positively influences event repeat participation. Given athletes spend much time and money training for, travelling to, and participating in the event, then repeat participation in the event could exist. Therefore, the following hypothesis was considered:

H5: Event behavioural intentions (i.e., repeat participation and positive WOM about the event) are positively associated with destination behavioural intentions (i.e., revisit for other leisure activities and positive WOM about the destination).

Method

Building on the literature described above, this study aims to address the following a three-fold gap: (1) how the event attributes, as those described above, influence event behavioural intentions (i.e., repeat event participation and positive word of mouth about the event) and destination behavioural intentions (repeat destination visitation and positive word of mouth about the destination), (2) how the destination attributes, as described earlier, will influence event behavioural intentions and destination behavioural intentions, and (3) how the event behavioural intentions influence destination behavioural intentions. Finally, with this knowledge, a discussion of how this information can be leveraged and cross-leveraged by the event owner and destination marketers to attain positive business outcomes – namely repeat event participation, repeat destination visitation, event WOM and destination WOM.

Procedure and questionnaire

Upon receiving ethics approval, an electronic survey was administered to active sport event participants via Amazon Mechanical Turk. Amazon Mechanical Turk (MTurk) is a marketplace that allows researchers to access a sample based on a specific set of criteria. In order to ensure validity using MTurk in this study, we set specific criteria questions to ensure sport tourists’ responses only (Thomas and Clifford, 2017). The screening questions asked respondents whether they had participated in a priority sport event within the last 6 months that was far enough distance that it an overnight stay away from their home was required. A priority event was the most important race they were training for in the season. Further explanation was given that a participation in active sport events was one that required the participant to engage in the sport activity, such as a 5 K, marathon, triathlon, bike race, etc. Anyone who did not meet the criteria of the screening questions was prevented from continuing on with the survey. There have been some concerns regarding the validity of MTurk, but a diverse range of replication studies have established that samples obtained though MTurk were just as valid as other sampling options (Buhrmester et al., 2011; Casler et al., 2013; Thomas and Clifford, 2017).

The solicitation email invited athletes to complete the survey if they had recently travelled to participate in an active sport event (within the last 6 months) that required an overnight stay, at minimum. Further explanation was given that an ‘active’ sport event requires the participant to have engaged in the sport activity, such as a 5 K, marathon, triathlon, bike race, etc. These active sport tourists were targeted because they had attended a specific sport event and could reflect on the experience to report whether they would repeat event participation and/or destination visitation. This purposive sampling approach allowed us to ascertain the perceptions of sport event travel from athletes who had recently participated in a priority race (Fricker, 2008). Amazon’s MTurk provides access to a broad range of participants who represent the study’s stated population (Redmiles et al., 2019).

The participants were asked to complete the online questionnaire taking no more than 15-minutes. Respondents were asked to assess the importance of sport event and destination attributes in the decision to participate in the sport event at the particular destination. The questionnaire consisted of items identified in the research on active sport event tourism (i.e. Aicher et al., 2020; Buning and Gibson, 2015, 2016a, 2016b; Getz and McConnell, 2011; Kaplanidou et al., 2012; Newland and Aicher, 2018) measuring preferences for event attributes (six items) and destination characteristics (six items). Behavioural intentions were measured with four items that asked the respondents to indicate the likelihood of revisiting the destination for leisure, returning to the same destination to participate in the event again, recommending the destination to others and recommending the event to others. Table 1 includes the descriptive statistics for the measures used in this study.

Table 1.

Descriptive results of measures.

Event Attribute	M	SD	Range
Reputation	5.27	1.41	1–7
History	4.86	1.55	1–7
Challenge	5.36	1.38	1–7
Cost	5.26	1.49	1–7
Scenery	5.01	1.55	1–7
Level of Competition	5.01	1.62	1–7
Destination Attributes	M	SD	Range
Shopping	3.74	1.73	1–7
Nightlife	4.1	1.71	1–7
Entertainment	4.5	1.74	1–7
Tours	4.37	1.74	1–7
Culture & art	4.6	1.64	1–7
Experiencing different cultures	4.73	1.67	1–7
Behaviours	M	SD	Range
WOM Destination	5.39	1.23	1–7
Return to destination	4.88	1.59	1–7
WOM Events	5.75	1.07	1–7
Return to event	5.32	1.52	1–7

Additionally, sport tourists answered sport training and demographic questions that included number of hours trained per week, level of competitor (novice/beginner, intermediate, advanced, elite), number of events participated per year (<3, 4–6, 7–9, >10), and event location (domestic or international). Sport training data were collected as research has shown differences in behaviour based on involvement (i.e., hours trained, number of events completed, etc.) in sport (Buning et al., 2018; Newland and Aicher, 2018). Demographic information included sport type, gender, ethnicity, education, and annual household income.

Data collection

Respondents returned 690 usable surveys. This United States based sample was approximately 57% of the respondents were male, white (68.1%), and highly educated with nearly half of the sample holding a bachelor’s degree (45.7%) or higher (27.2%). The majority of respondents (50.7%) considered themselves to be intermediate competitors. More than a half of the respondents (51.6%) have trained between 5 and 10 hours a week and with 29.4% training over 10 hours. A vast majority of them (83%) regularly travelled out-of-town to participate in active sport events. Table 2 provides the remainder of the demographic details.

Table 2.

Demographic details.

Characteristics	Descriptions	Statistics (%) (N = 690)
Age	18–29	41.2
	30–39	35.8
	40–49	15.8
	50+	7.2
Gender	Male	57.2
Gender	Female	42.8
Education	High School	6.5
	Some College	20.6
	Bachelor Degree	45.7
	Master Degree	21.3
	Terminal Degree	5.9
Household Income	<$29,999	23.5
	$30,000–59,999	31.3
	$60,000–99,999	28.4
	>$100,000	16.8
Ethnicity	White	68.1
	Black	9.0
	Hispanic	6.4
	Middle Eastern	1.9
	Asian	4.2
	Mixed ethnicity	7.1
	Other	3.3
Sport Event Type	Running Event	34.1
	Triathlon Event	31.6
	Cycling Event	11.3
	Charity Run/Bike/Walk	14.1
	Other endurance event	8.8
Level of competitor	Beginner	21
	Intermediate	50.7
	Advanced	22.8
	Elite/professional	5.5
Weekly hours trained	<5	19
	5.25–10	51.6
	10.25–15	18.7
	>15	10.7
Annual sport events	<3	40.7
	4–6	40.3
	7–9	8.4
	>10	10.6
Distance regularly travelled for priority sport event	Within 25mi of home	17.0
	Within 100mi of home (in state)	51.8
	Out of state	28.0
	Out of country	3.2

Data analysis

To test the extent to which the proposed variables (i.e., event attributes and destination attributes) influenced behavioural intentions of active sport event tourists, structural equation modelling (SEM) was utilised. Before testing the structural model, the reliability and discriminant validity of the four constructs (i.e., event attributes, destination attributes, event behavioural intentions, and destination behavioural intentions) were established. The internal consistency reliability of each construct was first measured by computing the composite reliability coefficients. According to Bagozzi and Yi (1989), all composite reliabilities should be above the 0.60 cut-off value. Since none of the values for all four constructs indicated less than 0.60, it can be said that the scale is reliable. Kline (2011) suggested that discriminant validity analysis can be confirmed when the estimated correlations of the constructs are not excessively high (>0.85) or excessively low (<0.1). The analysis results showed all values fell within the acceptable range, which supported the validity of the constructs.

Confirmatory factor analysis was used to assess the model’s four dimensions. Each construct was measured using the multi-dimensional scales: Event Attributes were measured by six items (i.e., reputation of the event; history of the event; challenge of the course; the event cost; scenic/interesting course; level of competition); Destination Attributes by six items (i.e., shopping; night life; entertainment; tours availability; cultural/historic attractions; chance of experiencing different culture); Event Behavioural Intentions and Destination Behavioural Intentions by two items (intention to participate in the event again; likelihood of recommending the event to others; intention to revisit the destination; likelihood of recommending the destination to others), respectively. As shown in Table 3, the proposed measurement model was found to fit to the data well by the following measures: comparative fit index (CFI), goodness of fit index (GFI), incremental fit index (IFI), and the root mean square error of approximation (RMSEA). Fit indices that exceeded 0.90 (CFI = 0.93; GFI = 0.93; IFI = 0.92) and RMSEA misfit indices at or lower than 0.06 (RMSEA = 0.06) are considered to indicate acceptable fit (Hu and Bentler, 1999).

Table 3.

Goodness-of-fit indices.

	χ²/df	CFI	IFI	GFI	RMSEA
Measurement Model	3.32	0.93	0.93	0.92	0.06
Structural Model	3.24	0.93	0.93	0.92	0.059
Suggested Value*	≤3	≥0.9	≥0.9	≥0.9	≤0.08

* Suggested values are based on Hair et al. (2006).

Results

Using Amos 22.0, structural equation modelling (SEM) was utilised to simultaneously examine the hypothesised relationships among the entire system of variables identified by the measurement model. Table 3 indicates that all goodness-of-fit indices supported an excellent fit of the structural model to the data: χ²/df = 3.24, CFI = 0.93, GFI = 0.92, IFI = 0.93, RMSEA = 0.06. The regression coefficient of each proposed association was positive and significant except the direct path from Event Attributes to Destination Behavioural Intentions (H2), as shown in Figure 1, attributes of the event were not found to be a direct predictor of intentions to revisit the destination for leisure and recommend the destination to others.

Figure 1.

Model testing research hypotheses. ________ Path significant at <.001, _ _ _ _ _ _ Path not significant. E1-Reputation of the event; E2-History of the event; E3-Challenge of the course; E4-Event cost; E5-Scenic/interesting course; E6-Level of competition; D1-Shopping; D2-Night life; D3-Entertainment; D4-Tours availability; D5-Cultural/historic attractions; D6-Chance of experiencing different culture; EBI1-Intention to participate in the event again; EBI2-Likelihood of recommending the event to others; DBI1-Intention to revisit the destination; DBI2-Likelihood of recommending the destination to others.

Event Attributes had a positive relationship with Event Behavioural Intentions (β = 0.32, p < 0.001), result which supported H1. Destination Attributes are significantly associated with Event Behavioural Intentions (β = 0.34, p < 0.001) and Destination Behavioural Intentions (β = 0.43, p < 0.001). These results supported H3 and H4. The last hypothesis (H5), stating that Event Behavioural Intentions are positively associated with Destination Behavioural intentions, are supported (β = 0.58, p < 0.001). The results of the analysis demonstrated a mediating role of Event Behavioural Intentions for both Event Attributes and Destination Attributes. Destination Attributes not only had a direct impact on Destination Behavioural Intentions (H4) but also are indirectly related to it through Event Behavioural Intentions (H3, H5). On the other hand, Event Attributes showed only an indirect relationship with Destination Behavioural Intentions facilitated by Event Behavioural Intentions (H1, H5). In other words, Event Attributes indirectly increased the likelihood of Destination Behavioural Intentions via Event Behavioural Intentions (H5) rather than affecting it directly (H2). In summary, the findings provided that all hypotheses were supported except for H2.

Discussion

A key concern for destination and event operators is whether the active sport event can be sustained and the degree to which it can generate flow on tourism, repeat visitation, and positive WOM (Aicher et al., 2020; Kaplanidou et al., 2012; Murphy et al., 2007; Taks et al., 2009). This study contributed to knowledge in a number of ways. First, the literature has provided a good picture of what destination elements drive repeat visitation, and what sport event factors motivate attendance, this study contributed to this knowledge by demonstrating an association between event and destination attributes and event behavioural intentions (repeat participation and WOM), that positively influenced destination behavioural intentions (revisit and WOM). Researchers have claimed that a strong event portfolio can provide a destination with a strong economic development tool – if leveraged properly (Chalip, 2004, 2006; Chalip and Leyns, 2002; Ziakas, 2014, 2019; Ziakas and Costa, 2011). Based on this outcome, it would suggest that event loyalty plays a role in destination loyalty. If destinations can build an integrated event schedule to sustain the attraction of visitors via event loyalty – who stay in the hotels, shop, explore, and eat in the restaurants – then destinations must strategically plan for how event loyalty can influence the entire event portfolio in order to be used as a complementary development tool for sustainable tourism (Ziakas, 2014, 2019; Ziakas and Costa, 2011). The development tool must be strategic as simply hosting a sport event does not guarantee the visitors will return to participate in the event again or visit the destination for future leisure activities. Therefore, it is critical that future research possibly focuses on a specific case study event to explore how event and destination attributes influence event and destination behavioural intentions so they can be leveraged for future participation and repeat visitation.

Next, this study contributed to knowledge by demonstrating the impact of event and destination attributes on behaviour. The model in this study illustrates that event and destination attributes had both direct and indirect effects on event and destination behavioural intentions. Although event attributes had no direct effect on destination behavioural intentions, the destination attributes did have a direct effect on destination behavioural intentions. This is an important finding for two reasons. First, it suggests that the event itself will not influence behaviour to return to the destination for future tourism (Aicher et al., 2020). This is important to destination leaders and operators to know as they cannot just depend on an event to attract future tourists. Second, the destination attributes do influence future intentions to return. The event is a great opportunity for destination marketers to highlight key tourism assets, like entertainment options, tours, the natural environment and the cultural experiences that align with the sport event attendees’ interests (Aicher and Newland, 2018; Chalip and McGuirty, 2004). A study of the regression coefficients associated with each path in the SEM model indicates that shopping, tours, and options that provide opportunities to experience the culture were of interest to the athletes in this study. These details are key when determining what destination assets could be cross-leveraged with athletes participating in the event. For example, if there are any upcoming cultural events, these should be promoted to participants as a means to encourage repeat visitation (Ziakas, 2010). This is a great opportunity to cross-leverage other key assets offered by the destination by introducing bundled packages of tourism activities at the point of the event registration can present the destination attributes to the sport event tourist prior to travel (Chalip and McGuirty, 2004; Newland and Aicher, 2018; Ziakas, 2010). Further, understanding personal resources (Yoo et al., 2020), athlete type (Aicher and Newland, 2018) as well as the level of immersion in the sport and travel conditions (Aicher et al., 2020; Buning and Gibson, 2016b) could help operators better bundle tourist activities. Doing so could enhance the participants’ experiences by adding value beyond the event, and positively influence the destination behavioural intentions in the future.

Destination leaders must be strategic in their policy-making as it relates to cross-leveraging tourism assets in order to ensure sustainable tourism practices after the sport event (Ziakas, 2019). One key leveraging tactic that may increase awareness and potentially secure future visitation is an invitation to return to the destination to engage in tourism activities at a discounted rate. As noted, cross-leveraging the other events that are a part of the destination’s event portfolio is a key promotional opportunity (Ziakas, 2010; Ziakas and Costa, 2011) that can maximise the destination’s exposure (Chalip and Costa, 2005). So, if the athlete fails to book tourism offerings during registration, the destination marketers can reach out after the event to invite the attendee to return for a different event or tourism activity (Ziakas, 2010). Local businesses and event directors from other events in the portfolio should also have a presence at the event to enhance the awareness of the tourism offerings (Chalip and Leyns, 2002; O’Brien, 2007). Given the results of this study showed a positive association between destination attributes and future destination behavioural intentions, it is critical that operators find ways to highlight the location’s business offerings, the event portfolio, and key tourism assets. This also provides a great opportunity for the local businesses to engage further with the event tourist and capture potential spending while the athlete is at the event (Chalip, 2018; Chalip and Leyns, 2002; O’Brien, 2007). Future research should build on Aicher and Newland’s (2018) work to continue to identify what destination attributes drive future tourism to an event destination and how marketers might capitalise on the event to build future tourism opportunities.

That the event attributes had no direct effect on the destination behavioural intentions was not surprising, as these are specific to the event itself (Newland and Aicher, 2018). If an athlete is travelling specifically for the elements the event offers, then it is unlikely these aspects would influence WOM for the destination or repeat visitation to the destination for other leisure activity. While there is no direct effect on the destination behavioural intentions, the event behavioural intentions mediated the relationship between event attributes and event behavioural intentions. Other studies have found that athletes who are highly immersed in their sport are unlikely to return to the event (Aicher et al., 2020; Buning and Gibson, 2016a; Buning et al., 2018), but are likely to engage in WOM activity (Kaplanidou et al., 2012; Newland et al., 2018). The findings from other studies are important, especially given that we know athletes that are highly immersed in their sport are less likely to return to the same event (Aicher et al., 2018, 2020; Buning et al., 2018). In this study, intending to participate in the event again is more highly associated with destination behaviour than WOM. This makes sense intuitively given repeat visitation to the destination is necessary for this to occur.

The final contribution to knowledge is repeat participation, which is information critical to event and destination operators. That athletes will repeat the event and engage in positive WOM is an important finding, especially with the knowledge that as athletes become more immersed in their sport, the less likely they are to repeat the event (Aicher et al., 2020; Buning and Gibson, 2016a; Buning et al., 2018), but they will talk about it (Kaplanidou et al., 2012; Yoo et al., 2020). If athletes are less likely to participate in the event again, then the event must deliver an exceptional experience so that athletes pass on their experiences to future event attendees. Therefore, the event owner must strategically plan for opportunities to capitalise on opportunities to attract a new yield of athletes based on WOM. Offering registration discount codes or other tactics that incentivise behaviour is key. Working closely with destination marketers to cross-leverage other events that could also be attractive to new athletes is critical.

It was expected that the destination attributes would positively influence the destination behavioural intentions. This finding aligns with other work in that favourable feelings about a destination can assist in decisions to visit a destination (Funk et al., 2007). While this finding seems to be common sense, it must be leveraged very carefully. As noted above, destination marketers and event managers should work very closely to develop packages that would interest the attendees to incite repeat visitation and interaction with the destination through other events or tourism assets (Aicher and Newland, 2018; Chalip and McGuirty, 2004; Ziakas and Costa, 2011). In this case, group tours, shopping, and the cultural experience were most highly associated with destination behaviour. It should not be assumed that an event attendee will return simply because they like the destination’s attributes. Event operators should make a strong effort to understand why athletes travel (Buning and Gibson, 2016a, 2016b; Getz and McConnell, 2011; Green, 2001) and what might motivate their other leisure travel (Aicher and Newland, 2018). Then, working in tandem with destination marketers, devise a plan to cross-leverage other events in the portfolio as well as tourism assets that can be bundled to extend stay, entice spend, and enhance the overall experience for the event attendee.

Limitations and future research

This study is not without limitations. First, while the attributes were based on the literature, there is no current validated measure for event and destination attributes. This limits our understanding of how event and destination attributes impact behaviour. At this point, items have been generated, but future researchers should consider new aspects of sport event tourism behaviour and any such attributes would have to be incorporated to ensure the valid measure of event and destination attributes in a given situation.

Also, there has been debate as to whether perception of event and destination attributes can be compared across a range of sport events (e.g., running, triathlon, cycling, swimming) when the elements of the events vary. Future research should explore across similar type event cases – e.g. comparisons of triathlon events only – to determine if there are behavioural differences among attendees of specific sport events. How these sport event tourism participants segment based on event and destination elements could be interesting to explore further (Aicher and Newland, 2018).

Conclusion

This study examined how event and destination attributes influence event and destination behavioural intentions and how this information could be leveraged by the event and destination. The results and the accompanying literature continue to point to the importance of collaboration between these two operators. One limitation of this study is that points of potential leverage between the event operators and destination marketers were not measured. An area for future research is to examine how event managers and destination leaders are collaborating in order to enhance future travel behaviour. Given this study’s perspective of better understanding the event attendee as a means for leveraging opportunities, future work should explore how well event owners understand their attendees’ interest in the destination and its tourism assets and other event offerings. Therefore, an exploration into the integration of the broader event portfolio into the sport event’s promotional efforts is warranted. Not only should the strategic efforts of both event and destination operators be explored, but it’s impact on the event participants’ actual future behaviour is critical. Future research should explore the impact on cross-leveraging of the destination’s events and tourism assets on actual event participant behaviour.

This study was unique in that it did not measure just one sport event, but rather had the athlete evaluate a recent active sport event. In doing so, we intended to explore a broader sample of active sport events, rather than one running or triathlon event, for example. Thus, the findings could perhaps be more generalisable to a range of events. Other research tends to examine one event in particular. While case research is important and convenient, results relate only to a specific destination and event. By broadening the context of the study to include a range of events and destinations, we could better understand the effect of attributes on behaviour. Of importance is how a better understanding the event attendees’ behavioural intentions as part of a leveraging strategy could help build synergy between sport events and destination marketers in order to capitalise on the opportunities and benefits each can provide the other.

Footnotes

Declaration of conflicting interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Brianna L Newland

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