Expanding Motivational Frameworks in Sports Tourism: Inclusiveness, Digital Interaction and Runner Segmentation in the Half Marathon Magaluf (Mallorca, Spain)

Abstract

Road running tourism events continue to grow worldwide and are increasingly leveraged by destinations seeking diversification and seasonality reduction. This study examines the motivational structure of participants in the 2025 Half Marathon Magaluf (Mallorca, Spain)—a mature Mediterranean resort undergoing tourism repositioning—and analyses how motivation-based segments relate to socio-demographic, sporting and tourism behaviours. Data were collected through a self-administered online survey (N = 306). An Exploratory Factor Analysis (EFA), followed by a Confirmatory Factor Analysis (CFA), validated a five-factor motivational structure: sport-related hedonism, socialisation, personal challenge, inclusiveness and digital interaction. A k-means cluster analysis identified five distinct segments—Digital Enthusiasts, Inclusive Enjoyers, Socializers, Hedonic Achievers and Inclusivists—each exhibiting differentiated patterns in Experience-Use History (EUH), origin, gender, and running-club membership. Notably, Socializers recorded the longest stays, Inclusive Enjoyers were overrepresented among first-time visitors, and Digital Enthusiasts and Hedonic Achievers included a higher share of international runners. These findings expand traditional motivational models by incorporating inclusiveness and digital interaction as emerging drivers and offer actionable recommendations for event organisers and destination managers seeking to enhance overnight stays and support destination repositioning strategies.

1. Introduction

Over the last decade, running events have consolidated as sites of sport participation and as instruments for tourist attraction, with significant economic and social impacts on destinations, hence the interest in understanding what drives participation and how those motivations translate into travel and consumption decisions (Barrios-Duarte & Cardoso-Pérez, 2002; Ramos-Ruiz et al., 2024; Drakakis & Papadaskalopoulos, 2014; Guereño-Omil et al., 2024). They have also emerged as relevant platforms for destination promotion and seasonal diversification, stimulating growing academic interest in understanding not only what drives participation but also how these motivations relate to individuals’ engagement with host destinations (Girginov et al., 2023).

Within this framework, Magaluf (Calvià, Balearic Islands) is a mature destination whose image has been the subject of critical reappraisals, ranging from mass low-cost British tourism at a turning point to narratives of risk and playful performativity (Casey, 2021; Davidson, 2023; Andrews, 2024). This trajectory is compounded by pronounced seasonality that conditions hotel profitability and has prompted diversification strategies through culture and sport events as levers for deseasonalization and destination repositioning, with residents displaying favorable attitudes toward sports tourism (Sánchez-Sánchez & Sánchez-Sánchez, 2025; Gomila, 2024; Rejón-Guardia et al., 2019; Bartolomé et al., 2009). In recent years, the Half Marathon Magaluf has become one of the flagship events within these strategies, attracting increasing national and international participation and generating a direct economic impact of over €1.2 million according to municipal reports (Ayuntamiento de Calvià, 2025).

The literature has described in detail intrinsic and extrinsic motives grounded in Self-Determination Theory (Ryan & Deci, 2000) and has employed instruments such as MOMS to map dimensions of health, personal achievement, and recognition (Masters et al., 1993; Yan & Ayatullah, 2021; Partyka & Waśkiewicz, 2024), as well as STMS to integrate sport, destination, and travel (Hungenberg et al., 2016). However, a clear research opportunity remains: to explicitly incorporate inclusion variables (age, gender, functional diversity) and digital interaction/validation as relevant motivations in contemporary running (Avello-Viveros et al., 2022; Koper et al., 2024; Stragier et al., 2018; Chaloupský et al., 2021; Couture, 2021; Van de Pol, 2023) and to connect these dimensions to observable tourist behaviors. Recent sociocultural dynamics, such as the increasing visibility of inclusive policies in endurance events and the rise in social media-driven participation, suggest that these emerging motives may play a meaningful role in shaping both how runners experience events and how they engage with destinations (Ramos-Ruiz et al., 2024; Wang et al., 2025).

At the same time, studies linking motivation with length of stay and expenditure show that casual profiles tend to stay overnight and spend more than those oriented exclusively toward competition, and that specific motives shape expenditure categories (Sato et al., 2018; Perić et al., 2019; Tzoumaka et al., 2022). However, few studies segment runners using a motivational framework that incorporates inclusion and digital interaction while simultaneously profiling differences in overnight stays, companions, and disaggregated expenditure (Parra-Camacho et al., 2019; Silva & Sobreiro, 2022). Moreover, the link between motivational profiles and participants’ level of destination familiarity, distinguishing between first-time and returning visitors, has been insufficiently examined, despite its importance for destination management (Parra-Camacho et al., 2019; Silva & Sobreiro, 2022; Sato et al., 2018; Perić et al., 2019; Higham & Hinch, 2018). This gap is consistent with broader work on experience-use history, which highlights the importance of prior engagement and familiarity with recreational settings in shaping participation patterns (Hammitt et al., 2004; Grofelnik et al., 2023).

On this basis, it is appropriate and timely to analyze the Half Marathon Magaluf, framed as a sporting event embedded in a mature Mediterranean destination undergoing processes of transformation and repositioning. This case enables (i) identifying motivational profiles that incorporate emerging dimensions such as inclusiveness and digital interaction; and (ii) examining how these profiles relate to participants’ tourism-related connection with the destination, particularly in terms of visitation patterns and familiarity.

Therefore, this research seeks to answer the following research question:

RQ: What motivational profiles can be identified among participants in the Half Marathon Magaluf, and how do these profiles relate to their tourism-related connection with the destination?

2. Literature Review

2.1. Motivations to Participate in Running Events and Their Measurement

The growing popularity of road running events over the last decades has turned them into a socially salient phenomenon, reflected in the continuous rise in participant numbers across distances ranging from 5 km to marathons and ultramarathons (Barrios-Duarte & Cardoso-Pérez, 2002; Ramos-Ruiz et al., 2024). This growth has stimulated sustained research interest in understanding what motivates individuals to register and train for these events.

A large proportion of this literature distinguishes between motivations that are more internally oriented (enjoyment, well-being, self-development) and those that are more externally oriented (social recognition, rewards, event prestige, destination appeal). Studies consistently highlight motives related to health, psychological well-being, self-esteem, and personal growth as central drivers of long-term adherence to running (Zhou et al., 2024; Koper et al., 2024; Partyka & Waśkiewicz, 2024), while also acknowledging the relevance of external factors such as socialisation, belonging to clubs, prizes, social recognition or the attractiveness of the host destination (Hrušová et al., 2024; An & Yamashita, 2024; Starzak & Sas-Nowosielski, 2019; Parra-Camacho et al., 2019).

Rather than testing a specific motivational theory, most empirical work in this area has operationalised these motives through dedicated instruments. The most influential is the Motivations of Marathoners Scales (MOMS) (Masters et al., 1993), originally composed of 56 items grouped into nine dimensions related to health (health orientation, weight concern), psychological aspects (self-esteem, life meaning, stress coping), social motives (affiliation, recognition) and achievement (competition, personal goals). MOMS has been adapted in various contexts and formats, including shortened versions and context-specific adaptations (Avello-Viveros et al., 2022; Barrios-Duarte & Cardoso-Pérez, 2002); and its factorial structure and psychometric robustness have been supported in multiple studies (Yan & Ayatullah, 2021; Akbaş & Waśkiewicz, 2025).

Beyond MOMS, several other instruments have been used to capture motivations in endurance and sport tourism settings, such as the Marathon Tourists’ Personal Development scale (MTPD) (Zhou et al., 2024), the Cyclist Motivation Instrument (CMI) (T. D. Brown et al., 2009), the Exercise Motivations Inventory (EMI-2) (Crofts et al., 2012), the PODIUM scale (Larumbe et al., 2015), or the Motives for Physical Activity Measure-Revised (MPAM-R) (Malchrowicz-Mośko et al., 2020). Particularly relevant for this study is the Sport Tourism Motivation Scale (STMS) (Hungenberg et al., 2016), designed to balance motivations related to sport, tourism and the destination. STMS comprises nine dimensions organised into two overarching blocks: sport-related motives (self-enrichment, skill mastery, social needs, physical condition, competitiveness) and tourism-related motives grounded in the push–pull framework (stress relief, exploration, destination attributes, landscape and tourism facilities). Recent applications of STMS in different running contexts show that physical condition, self-enrichment and social needs tend to be among the highest-rated motives, while also underscoring the importance of the natural environment and the tourism component in the runner’s experience (Guereño-Omil et al., 2024).

Taken together, this body of work indicates that running motivation is multidimensional and that sport-related, social, and tourism-related motives coexist. At the same time, most classic instruments were developed before the consolidation of contemporary debates on inclusiveness and digital interaction, and therefore only partially capture the motivational landscape of current mass-participation events.

2.2. Core Motivational Dimensions in Contemporary Running Events

Given the proliferation of instruments and scales, synthesising the main motivational dimensions relevant for contemporary road running is challenging (Crossman et al., 2024). Recent research, however, has converged on a set of key dimensions that reflect both long-standing and emerging motives. Ramos-Ruiz et al. (2024) identified five factors which offer an integrative framework sensitive to current sociocultural dynamics, including diversity policies and the widespread use of social media and fitness apps: sport-related hedonism, personal challenge, socialisation, event inclusiveness and digital interaction.

Based on this and related work, the present study focuses on five dimensions that are both theoretically grounded in previous literature and empirically meaningful for segmenting participants in mass running events.

2.2.1. Sport-Related Hedonism

Sport-related hedonism refers to the search for pleasure, enjoyment and positive emotions derived from participation in sport. Runners with high hedonic motivation engage in events because they find them fun, satisfying and emotionally rewarding, which, in turn, supports long-term adherence (Crofts et al., 2012; Ramos-Ruiz et al., 2024). Enjoyment has been identified as a primary determinant of sustained physical activity, often outweighing more instrumental motives such as health improvement or performance-oriented goals (Crossman et al., 2024).

Hedonic experiences associated with sport have both behavioural and psychological consequences. They are linked to improvements in mood and psychological well-being (Pereira et al., 2021) and can buffer against negative effects of prolonged effort or competitive pressure. Lack of enjoyment, by contrast, is closely associated with sport burnout and dropout (Krippl & Ziemainz, 2010). In this sense, pleasure is not a secondary by-product but an essential condition for continued engagement in running.

2.2.2. Personal Challenge and Self-Improvement

In the context of distance running, personal challenge often emerges as a central motivational dimension. It encompasses the desire to improve one’s performance, achieve personal bests, and test one’s limits (Akbaş & Waśkiewicz, 2025). While sometimes grouped under “competitive motivation” in earlier studies, recent evidence indicates that many runners frame their goals primarily in terms of self-improvement and mastery, even when external comparison is present (Nikolaidis et al., 2019; Ramos-Ruiz et al., 2024).

The salience of this dimension varies across profiles. Traditionally, men have scored higher on competitive motives than women (Malchrowicz-Mośko et al., 2020; León-Guereño et al., 2020), and younger, higher-performing and more experienced runners tend to report stronger performance-oriented motivation (Nikolaidis et al., 2019). However, more recent work suggests that women can exhibit equal or even higher motivation than men regarding personal challenge and improving personal records (Ramos-Ruiz et al., 2024). Overall, personal challenge and self-improvement are associated with more experienced and performance-oriented profiles, making this dimension particularly useful for segmentation in running events.

2.2.3. Socialisation

Socialisation is consistently identified as a key driver of participation in road running events. It includes motives such as belonging to a community, sharing experiences with friends or family, and enjoying a supportive group climate. Crossman et al. (2024) highlight social connectedness as especially salient among women and older adults, with participants valuing a positive and encouraging social environment.

Guereño-Omil et al. (2024) found that social needs ranked among the top three motivations for tourist runners, alongside physical fitness and self-enrichment. At the same time, the meaning and weight of socialisation vary according to distance and commitment. Among marathon runners, social interaction may be secondary and closely linked to community belonging and shared preparation (Partyka & Waśkiewicz, 2024), whereas in ultramarathon contexts the community becomes central to athlete identity and running is framed as a lifestyle that satisfies affiliation needs (Kazimierczak et al., 2020). Socialisation both stimulates initial participation and reinforces loyalty to the event and destination, which gives this dimension high managerial value in sports tourism.

2.2.4. Inclusiveness

The growing diversity of participants in mass running events has brought inclusiveness to the forefront as a distinct motivational dimension (Ramos-Ruiz et al., 2024). Contemporary races increasingly attract people with physical disabilities (Koper et al., 2024), older adults (Avello-Viveros et al., 2022), participants from varied sociocultural backgrounds (Barrios-Duarte & Cardoso-Pérez, 2002), and runners ranging from recreational to highly competitive (Malchrowicz-Mośko et al., 2020).

Motivations related to inclusiveness may involve valuing events that promote gender equality, accessibility for people with functional diversity, participation across age and experience levels, and openness to different socio-economic profiles (Larumbe-Zabala et al., 2019; Koper et al., 2024). Studies show, for example, that runners with disabilities are particularly motivated by self-esteem, psychological coping and health orientation rather than competition (Koper et al., 2024), while older runners often emphasise health, meaning in life and personal goals (Avello-Viveros et al., 2022).

Although inclusive policies and discourses have become more visible, structural barriers to full inclusion in running cultures remain (Smith-Tran, 2020). Recognising inclusiveness as a motivational dimension, rather than only as an organisational principle, is therefore important to ensure that events are not merely open in formal terms but also perceived as meaningful and welcoming by diverse participants. This dimension extends classic motivation models such as MOMS and STMS, which were developed before inclusion became a central concern in mass-participation sport.

2.2.5. Digital Interaction and Validation

Digital platforms, social networks and fitness applications have introduced digital interaction and validation as a salient component of the running experience. Applications such as Strava, RunKeeper or Endomondo not only record training data but also enable social interaction, comparison and gamification through likes, comments, leaderboards and challenges (Stragier et al., 2018; Van de Pol, 2023; Couture, 2021).

Stragier et al. (2018) distinguish between on-platform interaction (within the fitness community) and off-platform interaction (sharing content on external social networks). Socially motivated runners are more likely to share their activities externally to obtain social recognition, whereas achievement-oriented runners tend to focus on progress tracking, rankings and interaction within the specialised community. Digital interaction thus combines elements of socialisation, performance feedback and identity display, and can motivate participation both in training and in events.

Beyond these visible behaviours, other research shows that many users adopt low-participation–high-exhibition patterns, meaning they frequently post content but engage minimally with others’ posts (Gong et al., 2015). This aligns with broader evidence on silent or invisible audiences—users who consume content without reciprocating engagement (Bernstein et al., 2013). Such dynamics suggest that digital validation may be sought even in the absence of strong social interaction, making it a distinct motivational process within running communities. Thus, incorporating digital interaction as a distinct dimension acknowledges the increasing role of mediated social validation and virtual communities in shaping how runners experience and narrate their participation, an aspect largely absent from traditional scales like MOMS and STMS.

2.3. Motivation, Experience-Use History and Tourist Behaviour

Beyond participation itself, motivations influence how runners relate to host destinations. Research on sports tourism shows that motivation affects in-destination behaviour, including the combination of sport and leisure activities, patterns of exploration and spending (Tzoumaka et al., 2022; Perić et al., 2019). Sato et al. (2018) found that “casual” participants, who travel both for the event and for tourism, tend to spend more than “avid” participants focused primarily on competition. They also observed that cultural connection with the destination can strengthen engagement in tourist activities and increase total expenditure.

Perić et al. (2019) provide a more fine-grained view by examining how specific motives shape spending patterns. Trail runners motivated by nature contact tended to spend less, prioritising the intrinsic outdoor experience, whereas mountain bikers seeking stress relief spent more, combining the sporting challenge with other products and services at the destination. Overall, greater psychological involvement in physical activity has been associated with higher tourist expenditure (Sato et al., 2018), suggesting that sport-related motives condition consumption patterns at the destination (Drakakis & Papadaskalopoulos, 2014).

Complementing this, the experience-use history (EUH) approach emphasises the role of prior engagement and familiarity with recreational settings. Hammitt et al. (2004) show that repeated use and accumulated experience are linked to place bonding and substitution patterns, while Grofelnik et al. (2023) apply EUH to trail runners, demonstrating that prior experience with routes and destinations relates to environmental attitudes and travel behaviour. This perspective is particularly relevant for events held in tourism destinations, where differentiating between first-time and repeat visitors helps to understand how motivational profiles connect with destination familiarity and tourism-related engagement. In events such as the Half Marathon Magaluf, where local residents, domestic visitors and international runners coexist, motivations cannot be interpreted independently of this broader relationship with the destination.

2.4. Segmentation in Running Events

Segmentation has become a central approach for understanding the heterogeneity of participants in running events, as runners differ markedly in their motivational structures, sociodemographic profiles and event-related behaviours (Parra-Camacho et al., 2019; Silva & Sobreiro, 2022). Across studies, cluster analyses typically yield between three and five groups, generally organised around combinations of hedonism, self-improvement, socialisation, and degree of involvement or experience.

Research consistently identifies profiles mixing internal enjoyment and psychological benefits with varying emphases on social or competitive elements. Thus, Parra-Camacho et al. (2019) distinguished individualistic hedonists, enthusiasts, and socialised hedonists, differing in age, gender composition, socioeconomic status, and breadth of motivations. In trail running, Myburgh and Kruger (2021) found highly motivated all-in runners, performance-oriented profiles, and social-interaction-driven runners, illustrating how event type shapes the motivational mix.

Other segmentation studies incorporate psychological constructs, revealing further nuances. Tokarska and Rogowska (2025) identified intrinsically motivated, extrinsically motivated, and highly motivated groups based on the interaction between self-efficacy and motivation type. Similarly, Gillet et al. (2012) mapped profiles characterised by different combinations of autonomous and controlled motivation, linking them to performance and emotional exhaustion. Studies including involvement, loyalty and subjective well-being (Silva & Sobreiro, 2022) or pre-competitive anxiety (Prieto & González-García, 2022) show that behavioural engagement and emotional regulation also differentiate participants.

Additionally, segmentation based on event or destination attributes reveals differences linked to nationality, age and travel behaviour. Rejón-Guardia et al. (2023) identified clusters prioritising rest, social interaction, self-realisation, physical challenge or satisfaction with event services in the context of biking events. Murdy and Johnstone (2025) found profiles structured around spiritual and outdoor motivations, low engagement, or exploration and socialisation, showing that context shapes the motivational structure.

Taken together, the literature indicates that segmentation in running events yields stable motivational patterns, enriched by demographic and behavioural variation. This evidence supports the relevance of identifying motivational profiles that integrate emerging dimensions, such as inclusion and digital interaction, and examining how these profiles relate to participants’ tourism-related engagement with destinations, as addressed in the present study.

3. Methodology

3.1. Case Study: The Half Marathon Magaluf

Magaluf (Calvià, Mallorca) has been a paradigmatic enclave of mass low-cost British tourism, a model currently at a turning point and subject to critical reappraisal (Casey, 2021). Its public image has oscillated between narratives of risk and balcony incidents (Davidson, 2023) and playful re-readings that underscore the performativity of atypical tourism typologies (Andrews, 2024). This trajectory unfolds within the pronounced seasonality characteristic of Mediterranean resort destinations, a key determinant of hotel profitability and overall system efficiency (Sánchez-Sánchez & Sánchez-Sánchez, 2025). In response, diversification strategies have been promoted in which culture and events operate as levers for deseasonalization and experience enhancement (Gomila, 2024). Evidence from the Balearic Islands shows that small to medium-sized sports events with international projection can reduce seasonality and support destination repositioning (Rejón-Guardia et al., 2019). Residents also display favorable attitudes toward the development of sports tourism as a means of diversification (Bartolomé et al., 2009).

The Half Marathon Magaluf is a road running event held in Magaluf (Calvià, Mallorca, Spain) featuring two distances, 21 km and 10 km. In 2025 it held its ninth edition, allocating 1200 bib numbers for the main distances and 250 for minors. Approximately 60% of participants come from outside the island of Mallorca and, of these, about half are from other countries, with more than 50 nationalities represented (Half Marathon Magaluf, 2025b). Beyond attendance figures, the event incorporates explicit organisational attributes aligned with contemporary motivational dynamics, including: (i) strong socialisation components such as a pre-race “Pasta Party” and family-oriented activities (Half Marathon Magaluf, 2025d); (ii) structured youth participation through the Kids Run programme, reinforcing inclusiveness across age groups (Half Marathon Magaluf, 2025a); (iii) accessibility guidelines that promote equitable participation in accordance with municipal sustainability and inclusion policies (Línea Verde Calvià, 2024); and (iv) a notable digital presence, with active use of social media platforms for community building, performance sharing and virtual engagement (Half Marathon Magaluf, 2025c).

The race routes themselves integrate coastal and urban landscapes, enhancing the experiential dimension of participation and reinforcing symbolic connections between sport and destination identity (Half Marathon Magaluf, 2025e). These attributes collectively justify the relevance of analysing motivational profiles in this specific context, as the event operationalises social, digital and inclusive components that correspond to the emerging motivational dimensions examined in this study.

3.2. Survey Design

This study reports the results of a questionnaire administered to participants in the Magaluf half marathon held in 2025. Data were collected using a self-administered survey, a methodological approach shown to be suitable in prior research on sports tourism. The instrument (

Table 1. Questionnaire.

Code	Items	References
Sport-related hedonism		Algaba-Navarro et al. (2024); Crofts et al. (2012); Crossman et al. (2024); Krippl and Ziemainz (2010); Pereira et al. (2021); Ramos-Ruiz et al. (2024)
MOT01	To experience the enjoyment of this sport.
MOT02	To maintain or improve my physical fitness.
MOT03	To feel proud of finishing the race.
MOT04	To experience the emotions it evokes in me.
MOT05	To escape from my daily routine.
Inclusiveness		Avello-Viveros et al. (2022); Barrios-Duarte and Cardoso-Pérez (2002); Koper et al. (2024); Larumbe-Zabala et al. (2019); Ramos-Ruiz et al. (2024)
MOT06	To participate in an inclusive event.
MOT07	To participate in an event that is accessible to people with disabilities.
MOT08	To participate in an event that promotes gender equality.
MOT09	To participate in an event with runners of all ages.
Personal challenge/self-improvement/competitive motivation		Akbaş and Waśkiewicz (2025); Algaba-Navarro et al. (2024); León-Guereño et al. (2020); Nikolaidis et al. (2019); Ramos-Ruiz et al. (2024)
MOT10	The prestige of this competition motivates me.
MOT11	I want to improve my personal best.
MOT12	I want to be better than other participants.
MOT13	To compete with teammates from my running club.
MOT14	To achieve an optimal result given my preparation for the event.
MOT15	To win the race.
Socialisation		Algaba-Navarro et al. (2024); Crossman et al. (2024); Guereño-Omil et al. (2024); Kazimierczak et al. (2020); Partyka and Waśkiewicz (2024)
MOT16	To meet people with similar sporting interests.
MOT17	To socialize before, during, or after the event.
MOT18	To be able to talk about this event with friends or family in the future.
MOT19	For others to feel proud of me.
Digital interaction/validation		Couture (2021); Ramos-Ruiz et al. (2024); Stragier et al. (2018); Van de Pol (2023)
MOT20	I want to post photos or videos on my social networks.
MOT21	I want to receive likes on the photos or videos I post.
MOT22	I want to engage on my social networks in relation to my participation in this event.

) was developed with reference to previous studies on motivations to participate in sporting events (Ramos-Ruiz et al., 2024; Parra-Camacho et al., 2019).

The final questionnaire was structured into two sections. The first comprised items related to the motivational dimensions identified in prior research, adapted to the specific features of the event and the study’s objectives. In addition, exploratory items were incorporated, grounded in work on inclusive sport events (Darcy et al., 2017) and on social media behavior (Sheldon & Bryant, 2016). Following Hair et al. (2020), a 7-point Likert-type scale was employed. Value 1 indicated “totally disagree,” and 7 “totally agree”. The second section of the questionnaire collected sociodemographic information, including gender, age, educational level, occupational category, and income; as well as whether participants were members of a running club and questions related to their tourism behaviour. Such variables have been widely considered in prior research on participation in sporting events (Pereira et al., 2021; Qiu et al., 2020; Thuany et al., 2021).

The questionnaire was designed to ensure clarity, efficiency, and brevity in administration, thereby minimizing respondent fatigue (Hair et al., 2020). These considerations are essential to safeguard the reliability and validity of the data collected and to prevent potential difficulties during the fieldwork process (Moore et al., 2021).

3.3. Data Collection

A census sampling strategy was employed. The questionnaire was sent to the event organiser, who distributed it via email to the entire database of 1200 registered participants. This procedure ensured that the instrument reached only officially enrolled runners and that all responses originated exclusively from this population (Finn, 2012). The data were collected during the two weeks following the event, ensuring that participants’ responses reflected recent and accurate recall of their motivations and behaviours. In total, 306 valid questionnaires were obtained, resulting in a response rate of 25.5%.

3.4. Data Processing and Analysis

The analysis of responses and the verification of the study objectives were conducted through an Exploratory Factor Analysis (EFA) using SPSS Statistics v28 and Confirmatory Factor Analysis (CFA) using JASP v0.19. Reliability was initially assessed with Cronbach’s Alpha (α) (Cronbach, 1951) and McDonald’s Omega (ω) (McDonald, 1989) for the different dimensions of motivation, and all coefficients exceeded the recommended threshold of 0.70 (Nunnally & Bernstein, 1994). Before the factor analysis, we examined the distribution of Likert-type items to check normality using the Kolmogorov–Smirnov and Shapiro–Wilk tests (Kolmogorov, 1933; Smirnov, 1948; Shapiro & Wilk, 1965).

Exploratory Factor Analysis (EFA) is appropriate for examining and validating the latent structure of motivations, as it detects underlying patterns (Pérez & Medrano, 2010). The sample size met standard criteria by exceeding 300 cases (Tabachnick et al., 2007) and satisfying the rule of at least ten cases per item for the 22-item instrument (Nunnally & Bernstein, 1994), an approach used successfully in prior research on event participants’ motivations and behaviors (León-Quismondo et al., 2023; Kruger et al., 2016). Sampling adequacy was assessed with the Kaiser–Meyer–Olkin index, requiring values above 0.70 (Hair et al., 2020), and factorability was supported by Bartlett’s test of sphericity with p < 0.05 (Everitt & Wykes, 2001). Only factors with eigenvalues greater than 1 were retained (Kahn, 2006). Valid factors were required to include at least three items with loadings above 0.40 to ensure strong association with the corresponding dimension (Glutting et al., 2002), and the model was expected to explain at least 50% of the total accumulated variance (Merenda, 1997). A varimax rotation was applied to enhance interpretability and reduce cross-loadings. Items that did not meet these conditions were removed iteratively, after which Cronbach’s alpha and the factor structure were recalculated and the percentage of variance explained was compared with the initial solution to verify improvement.

To further validate the latent structure identified through the EFA, a Confirmatory Factor Analysis (CFA) was conducted using maximum likelihood estimation. CFA is appropriate for assessing the measurement model because it allows testing the factorial structure, item–factor relationships, and overall model fit against theoretically grounded expectations (T. A. Brown, 2015). Prior to estimation, multivariate normality was examined, and given the non-normal distribution of several items, robust maximum likelihood corrections were applied.

Model fit was assessed using widely accepted indices, including the Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Following Hu and Bentler (1999), acceptable fit was determined by CFI and TLI values above 0.90, RMSEA below 0.08, and SRMR below 0.08. Standardized factor loadings were required to exceed 0.40, and each latent dimension had to retain at least three items with significant loadings to ensure construct stability (Hair et al., 2020).

Reliability and validity were examined through composite reliability (CR) and average variance extracted (AVE). CR values above 0.70 and AVE values above 0.50 were considered evidence of internal consistency and convergent validity (Fornell & Larcker, 1981). Discriminant validity was assessed by verifying that the square root of AVE for each construct exceeded its inter-construct correlations.

Items that failed to meet loading, modification index or validity criteria were progressively removed, after which the model was re-estimated to ensure improved fit and factorial coherence. This iterative process ensured that the final measurement model was theoretically consistent, statistically robust, and aligned with the motivational dimensions assessed in this study.

A non-hierarchical cluster analysis was applied to segment the sample into homogeneous groups based on their Likert-scale ratings, a method that has proven useful in sport and tourism contexts (Martínez-Navarro et al., 2020). The algorithm was run with random initial seed selection and allowed to iterate until convergence, with stability achieved after X iterations. Cluster robustness was assessed through the within-cluster sum of squares (WCSS) and the F-values provided by the ANOVA table, which indicate the degree of separation among clusters. The resulting clusters were then profiled according to their sociodemographic characteristics and internal dimensions, and each group was assigned a label summarizing its main attributes.

Finally, associations between the resulting clusters and the categorical variables included in the study were examined using chi-square tests, and effect sizes were quantified using Cramer’s V, a robust measure of association commonly employed to assess the strength of relationships between nominal variables (Cohen, 1988).

4. Results

The average participant is a man aged 31 to 50, with a university education and a middle income. This participant does not reside in the host city and typically holds a job that does not require special physical demands.

Table 2. Socio-demographic profile of the sample.

Gender		Resident in Calvià, Magaluf, Mallorca
Male	57.7%	Yes	16.9%
Female	42.3%	No	83.1%
Age		Educational level
18 to 30 years old	18.2%	University degree completed	56.7%
31 to 50 years old	52.5%	University student	4.9%
More than 50 years old	29.3%	Any other situation	38.4%
Occupation		Monthly income
Related to physical activity job	14.3%	Very high	1%
Non-related to physical activity job	68.1%	High	5.5%
Retired	11.1%	Medium-high	27.7%
Any other situation	6.5%	Medium	46.3%
		Medium-low	13.4%
		Low	4.2%
		Very low	2%

details the sample’s sociodemographic characteristics and sporting profile.

Table 3. Descriptive statistics.

Sport-Related Hedonism			Inclusiveness			Personal Challenge			Socialisation			Digital Interaction
Items	Mean	SD	Items	Mean	SD	Items	Mean	SD	Items	Mean	SD	Items	Mean	SD
MOT01	6.62	0.701	MOT06	5.91	1.470	MOT10	5.40	1.574	MOT16	4.95	1.886	MOT20	4.43	2.245
MOT02	6.56	0.840	MOT07	6.01	1.418	MOT11	5.62	1.743	MOT17	5.02	1.876	MOT21	3.63	2.255
MOT03	6.67	0.776	MOT08	5.77	1.694	MOT12	3.90	2.084	MOT18	5.69	1.503	MOT22	3.86	2.238
MOT04	6.55	0.768	MOT09	6.42	1.117	MOT13	3.38	2.300	MOT19	5.30	1.882
MOT05	6.05	1.367				MOT14	5.90	1.371
						MOT15	2.67	2.087
α = 0.656			α = 0.879			α = 0.787			α = 0.769			α = 0.938
ω = 0.652			ω = 0.896			ω = 0.797			ω = 0.755			ω = 0.938

reports the descriptive statistics for motivation items, the sample’s Cronbach’s alpha (α) and McDonald’s Omega (ω). Kolmogorov-Smirnov test was used to assess normality. In all cases, the test yielded significance values below 0.05, confirming that the data do not conform to a normal distribution.

Items MOT03 (“to feel proud of finishing the race”) and MOT01 (“to experience the enjoyment of this sport”) show the highest means, above 6.6 points, indicating very high agreement among participants and suggesting that these hedonic aspects are central drivers of motivation. At the opposite end, MOT21 (“I want to receive ‘likes’ on the photos or videos I post”), MOT22 (“I want to engage on my social networks in relation to my participation in this event”) record low values, under the midpoint of the scale. However, these items collectively display the highest standard deviations, which suggests the need to examine them in greater depth and to verify whether there are groups of participants for whom this motivation is more relevant than for others. MOT15 (“To win the race”) shows the lowest means, indicating that these factors is less determinant in participants’ experience. The previous analysis of reliability records a value lower than 0.7 in the items related to sport hedonism. This data and variability provided a clear rationale for proceeding with a systematic refinement of the instrument through the subsequent factor-analytic procedures.

Successive runs of the statistical techniques progressively revealed the problematic items, and with each modification the results aligned more closely with the methodological criteria of the research. The first EFA was performed with all 22 items, and the model explained 64.232% of the total variance. Item MOT05 (“To escape from my daily routine”) was removed because it did not load above 0.40 on any factor. The second EFA was then conducted with 21 items, and the total variance explained increased to 66.019%. Item MOT19 (“For others to feel proud of me”) was removed, as it loaded above 0.40 on more than one factor; moreover, none of its loadings exceeded 0.50. The third EFA was performed with 20 items, and the total variance explained rose to 67.057%. Item MOT15 (“To win the race”) was removed, as it showed cross-loadings above 0.40 on multiple factors. This improved the total explained variance (67.699%) in the subsequent run with 19 items. In addition, item MOT10 (“The prestige of this competition motivates me”) was removed. The reasons were several: although its loading exceeded 0.40 (0.481), it remained below 0.50, and in the preliminary analysis its values of α = 0.656 and ω = 0.652, together with the differences in mean and SD compared with the other items in its dimension, indicated inconsistencies that could later compromise the CFA. Indeed, the total variance explained increased to 69.011%. This modification affected MOT13 (“To compete with teammates from my running club”), which for the first time showed cross-loadings above 0.40 on more than one factor. This item was removed, resulting in a 17-item instrument that explained 70.745% of the total variance. Finally, when conducting the CFA, it was observed that item MOT02 (“To maintain or improve my physical fitness”) negatively affected the factor, yielding an AVE value below the 0.50 threshold. Therefore, the item was removed. The final version of the instrument consisted of 16 items that explained 73.442% (

Table 4. Factor loadings, reliability and construct validity indicators.

Factors	Items	Load	Eigenvalue	EV (%)	Reliability	AVE	CR
Inclusiveness (1)	MOT07	0.886	3.017	18.854	α = 0.879 ω = 0.896	0.689	0.898
	MOT08	0.878
	MOT06	0.797
	MOT09	0.751
Digital interaction (2)	MOT20	0.903	2.715	16.969	α = 0.938 ω = 0.938	0.811	0.928
	MOT21	0.903
	MOT22	0.895
Socialisation (3)	MOT17	0.898	2.078	12.988	α = 0.797 ω = 0.821	0.625	0.829
	MOT16	0.839
	MOT18	0.603
Sport-related hedonism (4)	MOT04	0.814	1.981	12.379	α = 0.708 ω = 0.725	0.591	0.813
	MOT03	0.758
	MOT01	0.733
Personal challenge (5)	MOT11	0.791	1.960	12.253	α = 0.690 ω = 0.714	0.583	0.807
	MOT12	0.762
	MOT14	0.737

) of the total variance. The final EFA was considered valid as it met the methodological criteria established (Pizarro-Romero & Martínez-Mora, 2020). KMO = 0.814; χ² = 2549.716; df = 120; p = 0.000.

CFA confirmed that model fit was satisfactory and met the recommended thresholds set in Section 3. The chi-square test was significant (χ² = 223.433; df = 94; p < 0.001), as typically expected in samples of this size, so comparative and absolute fit indices were used to evaluate the model. The measurement model showed very good fit, with CFI = 0.948 and TLI = 0.934, both above the 0.90 criterion, and RMSEA = 0.067, with a 90% confidence interval [0.056, 0.078] and p-close = 0.007, indicating acceptable approximation error. Absolute fit was also supported by SRMR = 0.056 and a high GFI value (0.996). Additional incremental indices confirmed the robustness of the model (NNFI = 0.934, IFI = 0.949, RNI = 0.948).

Model stability was reinforced by Hoelter’s critical N, which showed adequate values (N = 162 at α = 0.05; N = 177 at α = 0.01). Standardized factor loadings all exceeded the minimum threshold of 0.40, and each construct retained at least three significant items, ensuring factorial stability. Composite reliability (CR) values were above 0.70 and average variance extracted (AVE) values exceeded 0.50 for all latent dimensions, demonstrating internal consistency and convergent validity. Discriminant validity was supported through the HTMT ratio, with all values below the conservative threshold of 0.85, confirming adequate separation among constructs.

Therefore, the model confirms a motivational structure based on five latent dimensions: three traditionally identified in the literature (sport-related hedonism, socialisation, and personal challenge), and two new ones which, on their own, account for nearly half of the total explained variance: inclusiveness and digital interaction.

This motivational structure was used to segment the sample, and five segments were identified that maximized between-group differences after 15 iterations. The distances between the final cluster centers ranged from 2.079 (clusters 1 and 2) to 2.870 (clusters 3 and 5). As shown in

Table 5. Cluster analysis. ANOVA table.

Factors	Cluster		Error		F	Sig.
	Sq. Mean	DoF	Sq. Mean	DoF
(1) Inclusiveness	41.457	4	0.462	301	89,665	<0.001
(2) Digital interaction	11.470	4	0.861	301	13,323	<0.001
(3) Socialisation	40.321	4	0.477	301	84,448	<0.001
(4) Sport-related hedonism	42.005	4	0.455	301	92,302	<0.001
(5) Personal Challenge	28.293	4	0.637	301	44,395	<0.001

, all motivational dimensions were significant in producing the segmentation.

Cluster 1 has been designated “Digital Enthusiasts,” since this segment records the highest scores in digital interaction together with strong sport-related hedonism and high inclusiveness, while personal challenge remains moderate. In contrast, Cluster 2 has been identified as “Inclusive Enjoyers,” as these runners show very high hedonism and inclusiveness, accompanied by high socialisation and low personal challenge. In turn, Cluster 3 has been termed “Socializers,” because this group combines high hedonism with high socialisation, while personal challenge is moderate and other dimensions are comparatively less relevant. Meanwhile, Cluster 4 has been labeled “Hedonic Achievers,” since they report the highest hedonism scores together with strong personal challenge and high inclusiveness, but low socialisation and low digital interaction. Finally, Cluster 5 has been named “Inclusivists,” as this group assigns the greatest importance to inclusiveness, above hedonism and far above socialisation, personal challenge and digital interaction.

From a tourist perspective (

Table 6. Characterization of each cluster.

Characterization	Cluster 1		Cluster 2		Cluster 3		Cluster 4		Cluster 5
	Digital Enthusiasts		Inclusive Enjoyers		Socializers		Hedonic Achievers		Inclusivists
	n = 108 (35.3%)		n = 44 (14.4%)		n = 37 (12.1%)		n = 65 (21.2%)		n = 52 (17.0%)
	Mean	SD	Mean	SD	Mean	SD	Mean	SD	Mean	SD
(1) Inclusiveness	6.75	0.626	6.61	0.956	3.78	1.656	5.81	1.473	5.91	1.132
(2) Digital interaction	5.53	1.697	3.14	2.143	3.17	2.195	3.15	2.160	3.03	1.851
(3) Socialisation	6.43	0.937	5.77	1.407	5.10	1.601	3.52	1.780	4.44	1.482
(4) Sport-related hedonism	6.86	0.396	6.80	0.531	6.51	0.883	6.89	0.327	5.67	0.953
(5) Personal Challenge	6.14	1.314	3.43	2.061	4.73	2.027	5.22	2.004	4.71	1.693
Gender (V = 0.207; p = 0.011) [n; %]
Male	64	36.16%	24	13.56%	24	13.56%	27	15.25%	38	21.47%
Female	44	34.11%	20	15.50%	13	10.08%	38	29.46%	14	10.85%
Educational level (V = 0.162; p = 0.042) [n; %]
University degree	47	27.17%	29	16.76%	21	12.14%	44	25.43%	32	18.50%
Any other situation	61	45.86%	15	11.28%	16	12.03%	21	15.79%	20	15.04%
Members of a running club (V = 0.179; p = 0.044) [n; %]
Yes	33	44.00%	9	12.00%	8	10.67%	8	10.67%	17	22.67%
No	75	32.47%	35	15.15%	29	12.55%	57	24.68%	35	15.15%
Residence (V = 0.202; p = 0.011) [n; %]
Resident in Calvià	21	40.38%	3	5.77%	6	11.54%	11	21.15%	11	21.15%
Rest of Mallorca island	51	41.13%	11	8.87%	14	11.29%	29	23.39%	19	15.32%
Rest of Balearic Islands	0	0.00%	1	50.00%	0	0.00%	1	50.00%	0	0.00%
Rest of Spain	7	33.33%	10	47.62%	0	0.00%	1	4.76%	3	14.29%
Foreign country	29	27.10%	19	17.76%	17	15.89%	23	21.50%	19	17.76%
First time visiting Calvià (V = 0.246; p = 0.004) [n; %]
Resident in Calvià	21	40.38%	3	5.77%	6	11.54%	11	21.15%	11	21.15%
Yes	19	23.46%	22	27.16%	13	16.05%	14	17.28%	13	16.05%
No	68	39.31%	19	10.98%	18	10.40%	40	23.12%	28	16.18%
Length of stay (V = 0.199; p = 0.019) [n; %]
Days spent in Calvià	2.78		3.22		3.48		3.09		3.17

), Cramer’s V values ranged from 0.162 to 0.246, indicating weak to weak-moderate but statistically significant associations between cluster membership and key sociodemographic and behavioural variables. The strongest associations were observed for destination familiarity (first-time vs. repeat visitors, V = 0.246; p = 0.004) and place of residence (V = 0.202; p = 0.011). In the same vein, the segmentation was also externally validated through length of stay (V = 0.199; p = 0.019). Thus, individuals visiting Calvià for the first time are more prevalent in the “Inclusive Enjoyers” cluster, whereas tourists already familiar with the destination tend to concentrate in the “Digital Enthusiasts” cluster.

Proximity sport tourists—those residing in other municipalities on the island of Mallorca—also tend to cluster within the “Digital Enthusiasts” group. Peninsular Spanish tourists, however, are primarily concentrated in the “Inclusive Enjoyers” cluster. Foreign tourists, in contrast, although most strongly represented in the “Digital Enthusiasts” cluster, also appear in high proportions within the “Hedonic Achievers” cluster. The “Socializers” cluster shows the longest stays in the destination, standing in clear contrast to the “Digital Enthusiasts,” whose length of stay is affected by the lower overnight rates typical of proximity tourism.

From the perspective of sociodemographic and sport-related characteristics (Table 6), the variables gender, educational level, and membership in a running club were significant for externally validating the clusters. After the “Digital Enthusiasts” cluster—unsurprising given its size—men tend to concentrate in the “Inclusivists” cluster, whereas women are more prevalent in the “Hedonic Achievers,” a pattern also observed among university graduates (25.43%) and among individuals who do not belong to a running club (24.68%).

5. Discussion

The findings of this study confirm a multidimensional motivational structure composed of five latent dimensions: sport-related hedonism, personal challenge, socialisation, inclusiveness and digital interaction. These dimensions reflect both established patterns and emerging dynamics in contemporary running events. The inclusion of inclusiveness and digital interaction as statistically robust dimensions demonstrates that traditional frameworks such as MOMS (Masters et al., 1993) and STMS (Hungenberg et al., 2016) no longer fully capture the motivational landscape. Inclusiveness aligns with the growing relevance of equity, accessibility and diversity in mass-participation sport (Koper et al., 2024; Larumbe-Zabala et al., 2019), while digital interaction reflects practices of mediated validation, gamification and identity projection characteristic of current social media usage (Stragier et al., 2018; Van de Pol, 2023). The wide dispersion of responses in digital interaction is consistent with a low-participation/high-exhibition model (Sheldon & Bryant, 2016), reinforcing the need to recognise this dimension independently rather than as a subset of social motives.

Building upon this structure, the cluster analysis identified five segments: Digital Enthusiasts, Inclusive Enjoyers, Socializers, Hedonic Achievers and Inclusivists. This reveals differentiated ways in which runners integrate traditional and new motivational drivers. Two segments, Digital Enthusiasts and Inclusivists, represent profiles not observed in prior segmentation studies (Parra-Camacho et al., 2019; Myburgh & Kruger, 2021), showing that the incorporation of inclusiveness and digital interaction enables finer-grained segmentation. The remaining clusters partially mirror previously identified hedonic, social and achievement-oriented profiles but are further differentiated by the new motivational dimensions.

Behavioural differences reinforce the explanatory relevance of motivation. Applying the Experience-Use History (EUH) perspective (Hammitt et al., 2004; Grofelnik et al., 2023), the study finds that first-time visitors concentrate in Inclusive Enjoyers, whereas Digital Enthusiasts show stronger representation among repeat visitors, indicating that familiarity may facilitate digitally mediated place-related expression. Socializers recorded the longest stays, supporting the idea that socially oriented motivations translate into greater tourism engagement (Sato et al., 2018; Perić et al., 2019). These patterns demonstrate that motivational profiles shape not only event participation but also tourism-related behaviour in measurable ways.

Within the specific context of Magaluf, the event’s organisational features, such as explicit inclusiveness policies, structured socialisation opportunities and a strong digital presence, align with the motivational dimensions identified. This correspondence suggests that the Half Marathon Magaluf functions as an operational platform through which the destination can activate different motivational segments, supporting diversification and deseasonalisation strategies (Rejón-Guardia et al., 2019; Bartolomé et al., 2009). Importantly, the distribution of segments across origin groups (locals, proximity sports tourists, domestic and international visitors) provides relevant information on how runners connect with the destination depending on their motivational profile.

Finally, the methodological process strengthens confidence in the findings: the iterative refinement of the measurement instrument, successful CFA validation and the stable five-cluster solution all contribute to a robust segmentation framework supported by sociodemographic and behavioural indicators. Together, these results underscore the relevance of incorporating inclusiveness, digital engagement and destination familiarity into contemporary motivational and segmentation models for running events.

6. Conclusions

6.1. Theoretical Contribution

This study advances motivation research by validating a five-dimensional structure that integrates two emerging drivers—inclusiveness and digital interaction—absent from traditional models. These findings extend established motivational frameworks and demonstrate that equity-oriented values and mediated social validation now constitute independent components of runners’ decision-making. The integration of the Experience-Use History (EUH) perspective offers a theoretically grounded bridge between motivation, destination familiarity and behavioural engagement, enriching current approaches to sport tourism in mature destinations.

6.2. Empirical Contribution

Empirically, the study provides a validated 16-item scale and identifies five distinct motivational segments. These clusters differ systematically in motivational emphasis and tourism behaviour, demonstrating clear associations with first-time visitation, length of stay and origin. The segmentation thus offers a refined behavioural typology for understanding how different groups experience both the event and the destination.

6.3. Managerial Implications

The segmentation obtained in this study offers clear opportunities for tailoring event and destination strategies according to the motivational profiles of participants. Each cluster reflects different expectations toward the event and distinct patterns of tourist behaviour, making differentiated management both necessary and beneficial for Calvià.

Digital Enthusiasts, with strong digital engagement and relatively short stays, represent a high-potential group for destination visibility. Encouraging user-generated content through digital challenges or curated photo points can amplify promotion, while targeted weekend packages may help extend their overnight stays.

Inclusive Enjoyers, overrepresented among first-time visitors, respond strongly to social and inclusive attributes. Strengthening family-friendly activities, inclusive messaging and pre-/post-race social events could increase the likelihood of bringing companions and converting them into repeat visitors.

Socializers stay the longest in the destination, making them especially valuable for local expenditure. Enhancing community-building initiatives, such as club meet-ups or social gatherings, may reinforce their engagement and stimulate additional in-destination consumption.

Hedonic Achievers, many of whom are international runners, combine enjoyment with strong performance goals. Offering pacing services, technical briefings and premium recovery or leisure experiences may increase their satisfaction and overall spending, while reinforcing Calvià’s positioning among foreign markets.

Inclusivists prioritise inclusiveness above all other motivations. Strengthening accessibility measures, inclusive policies and partnerships with relevant associations can enhance their experience and encourage the presence of accompanying visitors. Given their low digital engagement, offline communication channels may be more effective.

Altogether, adapting event design and marketing to these distinct profiles provides a strategic pathway for increasing overnight stays, attracting companions, stimulating tourist expenditure and fostering repeat visitation, thereby supporting Calvià’s broader objectives as a mature destination seeking diversification and reduced seasonality.

6.4. Limitations

Limitations include the use of a non-probabilistic sample, the inability of the instrument to capture certain outdoor motivations such as nature enjoyment, the cross-sectional design, and reliance on self-reported digital behaviour. Moreover, the study focuses on a single event, which may introduce biases associated with the specific profile of its participants and limit the generalisability of the findings to other running contexts.

6.5. Future Research

Future studies could incorporate nature-based and environmental motivations, assess the stability of the segments across editions and destinations, integrate behavioural data from fitness apps or social platforms, analyse long-term destination loyalty effects, and test experimentally how changes in event attributes influence behaviour and economic impact. From a cultural perspective, replicating the study in other regions of Spain and in different international contexts would allow researchers to identify potential deviations linked to the specific participant profiles of each event. From a methodological standpoint, future research could also benefit from predictive analytical approaches, such as PLS-SEM or multilayer perceptron artificial neural networks (ANN), to model the causal structure of motivations and to forecast behavioural outcomes with greater precision.