Corsa, Turismo e Inclusione: Motivational Structure and Participant Segmentation at the Neapolis Marathon (Naples, Italy)

Abstract

This study analyzes the motivational structure and participant profiles in the 2025 Naples Half Marathon. A questionnaire was administered to 791 runners, and exploratory and confirmatory factor analyses were applied, followed by cluster analysis. The results identified a final structure of 19 items grouped into five dimensions: inclusion, socialization, sports hedonism, destination appeal, and competition. Inclusion presented the highest explanatory capacity, confirming the relevance of diversity, accessibility, and equitable participation values in running events. Segmentation allowed for the identification of three profiles: Inclusive Experimenters, Hedonists, and Enthusiasts. These groups differed mainly in the intensity and combination of their motivations, while associations with gender were weak and non-significant. Enthusiasts constituted the majority group and showed high scores across all dimensions, whereas Inclusive Experimenters stood out for inclusion and destination appeal. The findings expand the understanding of the runner’s experience and offer implications for the management of sporting events and tourism destinations.

1. Introduction

In recent decades, participation in endurance running events has established itself as one of the most representative forms of popular sport and active leisure on a global scale [1]. This phenomenon, which has now taken on a social dimension, has driven the sustained growth of long-distance events such as the marathon and the half-marathon [2]. Beyond the physical activity itself, these events have emerged as powerful tools for attracting tourists and promoting destinations, linking urban landscapes with immersive cultural experiences that allow participants to escape their daily routines [3]. In this context, understanding the motivations that drive runners is crucial for sports psychology and for managers and marketing professionals to achieve effective market segmentation that fosters long-term engagement and optimises the tourism potential of destinations [4].

The scientific literature has addressed this motivational heterogeneity through various theoretical frameworks [5,6,7]. However, recent research suggests that the motivational structure is not static: whilst novice runners tend to seek external validation and personal achievement, more experienced and long-distance runners tend to prioritise intrinsic rewards, a sense of purpose and emotional well-being [8,9,10].

Previous research has established that participants in running events are motivationally heterogeneous. Studies have identified distinct profiles based on traditional motives such as personal enjoyment, socialisation and competition, as well as on broader dimensions including commitment, loyalty and well-being [11,12]. More recent research in the Magaluf and Elche half-marathons has extended these approaches by incorporating emerging dimensions such as inclusion and digital interaction, producing differentiated participant profiles [13,14]. However, the studies use different combinations of motivational dimensions and focus on specific event contexts. It therefore remains unclear how the motivational structure of an international urban running event such as the Neapolis Marathon is organised and how its dimensions combine to differentiate participant profiles.

Against this background, the present study aims to examine the motivational structure of participation in the 2025 Neapolis Marathon and identify distinct participant profiles. Its specific analytical objective is to assess whether five theoretically informed domains (sports hedonism, socialisation, competition, inclusion and destination appeal) are empirically distinguishable. As the analysis is exploratory, it does not assume that all five domains will emerge as separate dimensions. Accordingly, the study addresses two research questions:

RQ1: 

What motivational structure characterises participation in the event?

RQ2: 

What distinct participant profiles emerge from the motivational dimensions retained in the analysis? The resulting profiles are also described in relation to participants’ sociodemographic characteristics.

2. Literature Review

2.1. Theoretical Framework

This study is primarily based on the push–pull approach proposed by [15]. This model posits that tourist behaviour and the choice of a destination or event are explained by the interaction between two types of factors. Push factors are internal in nature and relate to needs, desires or psychological states that drive the individual to participate. Pull factors, by contrast, correspond to the external characteristics of the destination or event that guide and determine the choice between different alternatives [15].

When applied to running events, this approach allows us to distinguish between the personal motives that predispose a runner to participate and the specific attributes that make a particular event attractive. The usefulness of the push–pull approach has been supported by research on sports tourism and endurance events. These studies show that participants do not travel solely to complete a race, but also to experience emotions, escape the daily routine, improve their well-being, forge social connections and discover new destinations [16,17,18]. At the same time, the characteristics of the event and the local area—such as the urban environment, cultural offerings, accessibility and the opportunity to engage in tourist activities—help to distinguish one event from another and can influence satisfaction, repeat visitation and loyalty to the destination [3,19].

From this perspective, the dimensions analysed in this study can be linked to both types of factors. Sporting hedonism and competition primarily represent push motives, as they express the enjoyment, emotions and desire to excel that runners seek to experience. Socialisation also contains a push component, related to the need for affiliation and a sense of belonging, although it equally depends on the opportunities for interaction offered by the event. Inclusion can act as a pull factor when runners perceive that the race promotes equality, diversity and the participation of people of different ages, genders and abilities [14,20,21]. The dimension of destination appeal can be interpreted primarily as a pull factor. This dimension encompasses interest in the landscape, the urban environment, cultural activities and complementary experiences that take place outside the competition. In this way, the sporting event acts as a gateway to the destination, whilst its tourism resources help to enhance the overall appeal of participation [3,17].

2.2. Motivation to Participate in Sporting Events

In recent decades, participation in events such as the marathon has seen sustained growth, establishing itself as a global social phenomenon that transcends mere recreational practice [1]. Understanding this mix of reasons is essential for marketing professionals and sports managers to achieve effective market segmentation and foster ongoing engagement in long-distance running [4].

Scientific research has addressed this heterogeneity through various theoretical frameworks, notably Self-Determination Theory (SDT), Serious Leisure Theory and Flow Theory [5,6,7]. The use of validated instruments, such as the Motivations of Marathoners Scale (MOMS), has enabled the identification of core factors including psychological coping, recognition, competition, health, affiliation and concern about weight [22].

The specialist literature indicates that motivational structure is a construct that evolves in accordance with accumulated experience and the distance of the race. Novice runners tend to be driven predominantly by extrinsic regulation, external validation and tangible goals focused on health and weight control [8,9]. In contrast, marathon runners and endurance athletes demonstrate a greater commitment to competitive and social dimensions, integrating intrinsic motivations linked to self-esteem and a sense of purpose [23]. In the context of extreme distances, such as ultramarathons, the motivational focus shifts towards deep psychological processes, centred on personal growth, the management of emotional challenges and the search for an existential purpose through running [10]. Unlike short-distance runners, these athletes prioritise psychological coping and a sense of purpose over external recognition [9].

As elite athletes, marathon tourists seek personal development and the accumulation of social capital through sport [18,24]. This practice fosters prosocial behaviour [25] and contributes to the formation of a social identity and a distinctive subculture within the realm of ‘serious leisure’ [26,27].

2.3. Socialisation

Socialisation is a cross-cutting theme in sporting motivation, constantly interacting with personal and environmental factors [28,29] The scientific literature identifies social affiliation as a fundamental psychological need that sporting events help to satisfy [30], with social connections and a positive group environment being key determinants of adherence to the activity [31,32]. This social significance remains consistent across various profiles of runners [22,33].

To ensure continued participation in sport into adulthood, the structure of social and organisational support is a determining factor [34]. In this regard, autonomous motivation and self-regulation must be underpinned by robust social support [6]. This need for a sense of belonging is particularly pronounced in specific populations: whilst for novice runners, the community context is key to initial motivation [35], for veteran ultra-marathon athletes, social identity and affiliation become critically important for maintaining their commitment to the sport [26]. Finally, it is worth noting that, in the post-pandemic landscape, socialisation has established itself as one of the essential and unifying dimensions of the new sporting motivation [36].

2.4. Hedonism

The scientific literature has identified enjoyment as a fundamental pillar of sport psychology. The theory of sporting commitment already regarded enjoyment as a key element in understanding the individual’s connection to physical activity [37]. In this regard, it has been shown that enjoyment acts as a determining factor in sustaining active participation following the conclusion of specific events [38] and is an essential element in maintaining physical activity in the long term [39].

The motivations behind exercise vary significantly depending on the participant’s profile. [40] note that, whilst athletes are primarily motivated by competition and enjoyment, non-athletes prioritise mood and appearance. However, in general terms, personal enjoyment and psychological achievement emerge as the most highly valued motivational factors [11]. Furthermore, personality variables influence this experience: runners with high conscientiousness tend to find greater enjoyment and meaning in running [41].

The significance of sporting hedonism is evident from the earliest stages of development. For children, enjoyment and fun are the primary reasons for engaging in physical activity [42], these being the main factors identified, for example, in 12-year-olds who practise athletics [30]. In adolescence, motivation becomes more complex, combining enjoyment with health, body image and escapism [43]. Finally, in adulthood, enjoyment and health benefits remain the most common reasons for participating in organised sport [34], emerging as the main individual factors facilitating continued participation in sport [44].

The recreational aspect of sport is also intertwined with the social experience and the environment. In the field of sports tourism, the main motivations include physical challenge, personal development, social interaction and escape [4]. In the case of road cyclists, socialisation and escapism take on greater significance [16]. Recent research suggests that, on occasion, social motivation and the collective enjoyment experienced during the ride carry greater weight than the race itself in explaining the intention to repeat the experience [19]. Similarly, personal achievement and escapism are key benefits sought by participants in sporting events [45], where commitment, enjoyment and health jointly predict the intention to participate again [4].

2.5. Competition

Competition, understood as a personal challenge and the desire to excel, constitutes one of the primary sources of motivation in sport [46]. According to Self-Determination Theory, it is posited that the fulfilment of basic psychological needs (autonomy, competence and social relatedness) is essential to facilitate the internalisation of meaningful activities and foster sustained motivation [6,47]. Within this framework, the perception of competence triggers the desire to compete [48] and contributes directly to the formation of athletic identity and the improvement of self-image [49,50].

The scientific literature establishes a direct relationship between performance level and motivational orientation. Runners with higher performance levels and faster paces tend to be more strongly oriented towards personal achievement and competition [30,46], which correlates with greater perceived competitiveness [51]. Those with a strong competitive orientation tend to train more frequently and pursue goals based strictly on results [22,52]. However, a distinction must be made between harmonious passion, which supports well-being, and obsessive passion, which can lead to overtraining or exercise addiction due to excessive competitiveness [53,54,55].

The significance of the competitive dimension varies considerably depending on a range of individual variables. In terms of gender, the classical literature suggests that men score higher on competitive motives and personal goals, a trend sometimes attributed to evolutionary pressures [46,56]. Conversely, women’s participation in sport has traditionally been linked to a prioritisation of psychological well-being, social connection and coping strategies [30]. However, recent findings qualify this distinction by suggesting that women exhibit comparable, or even greater, motivation with regard to personal challenge and the optimisation of their individual performance [21].

Furthermore, age exerts a decisive influence on motivational orientation; interest in competition and external recognition tends to decline with age, leading to a shift towards goals centred on health, boosting self-esteem and general well-being [8,57,58]. Finally, an athlete’s level of experience shapes the focus of their participation: whilst novice runners are primarily driven by external recognition, experienced and veteran runners orient their practice towards self-actualisation, mastery of the activity and intrinsic personal challenge [59,60].

Despite the prevalence of competition in certain groups, there is a trend amongst recreational runners towards moving away from norms centred exclusively on performance, prioritising autonomy and enjoyment [61]. In this context, personal challenge emerges as a central dimension that frames objectives in terms of self-improvement and testing one’s limits, even in environments of external comparison [21,59]. This distinction is crucial for the segmentation of events, as more experienced participants tend to closely link personal challenge with improving their personal bests [14].

2.6. Inclusion

The conceptualisation of inclusion in sporting events has undergone a significant evolution, shifting from an approach focused strictly on physical accessibility towards a comprehensive model where diversity lies at the heart of the participatory experience [62]. Whilst early studies linked inclusion primarily to charity events [63,64], contemporary research proposes recognising inclusion as a primary motivational dimension, capable of expanding the classical theoretical frameworks of sporting motivation [20,21]. Nowadays, mass-participation races encourage diversity amongst participants, attracting people with functional diversity [20], older adults [65] and participants from diverse socio-cultural backgrounds and competitive levels [30]. Events designed to be accessible encourage healthy habits among previously inactive populations [30], reduce social barriers and promote equity and social justice as intrinsic motivational factors [66,67].

The gender perspective adds an additional dimension to the study of inclusion. Ref. [21] observed that women attached greater importance than men to the inclusive nature of the event, particularly in aspects relating to gender equality and the participation of people with functional diversity. Similarly, ref. [68] found that female participants in triathlon events placed greater importance than men on a sense of unity and integration with others, social recognition and a sense of belonging to the sporting subculture. In contrast, men placed greater value on the perception of equality during the competition.

Despite the prominence of inclusive discourse, structural barriers persist that hinder full integration into running culture [69]. It is therefore imperative that events go beyond formal openness and are perceived as meaningful spaces for all socio-economic and age groups [13]. The perception of an inclusive environment strengthens community cohesion and prosocial values [62] and, furthermore, increases participants’ loyalty and their intention to return to the event [70]. Finally, from a territorial perspective, a commitment to diversity enhances the destination’s social reputation and attracts a more diverse audience [71], consolidating inclusion as an essential link between sport and social sustainability [72,73].

2.7. Tourist Motivation/Destination Appeal

The scientific literature emphasises that environmental characteristics are key factors that directly influence participation in and enjoyment of leisure activities [74]. In outdoor sports disciplines, exploring the environment is established as a key motivational factor [28], particularly when the natural environment acts as a source of wellbeing [75] that enhances the restorative value of the sporting experience [76]. This synergy between sport and nature benefits both the individual and the sustainable development of the destination [77].

From an experiential perspective, sports tourism offers more intense emotional experiences than practising in one’s local environment. In this context, the pursuit of thrills emerges as the main motivation for runner-tourists [17], whilst specific forms such as marathon tourism foster processes of self-exploration and psychological wellbeing [3,10]. At a sociodemographic level, it is observed that runners with higher incomes and greater work flexibility invest more heavily in both the events themselves and the associated tourism [78]. Finally, the literature suggests that sports tourists’ satisfaction is a critical predictor of loyalty, as satisfied participants tend to return to both the destination and the event in future editions [79].

2.8. Segmentation of Participants

Segmentation has established itself as a central analytical approach for addressing the intrinsic heterogeneity of participants in running events. This premise enables an understanding of how runners differ significantly in their motivational structures, sociodemographic profiles and event-related behaviours [11,12]. The literature suggests that segmentation yields stable motivational patterns, enriched by demographic and behavioural variations, which supports the need to identify profiles that integrate emerging dimensions and their relationship with tourism engagement in destinations [13].

In the field of urban road races, ref. [11] identified three distinct motivational profiles. ‘Individual Hedonists’ are primarily oriented towards psychological well-being, personal satisfaction and the physical benefits of running, attaching less importance to competition, social recognition and material rewards. ‘Enthusiasts’ rate most of the analysed dimensions positively, including enjoyment, socialising, competition and interest in events. Finally, “Socialising Hedonists” combine a high regard for personal well-being with a significant focus on social interaction and participation in races.

For their part, ref. [80] identified three distinct groups of runners based on their level of commitment to the activity. ‘Highly Committed Runners’ display a high level of enthusiasm for running, a higher training frequency, a greater weekly mileage, more experience in long-distance events and greater membership of sports clubs. ‘Moderately Committed Runners’ display a positive, albeit more balanced and recreational, attitude towards the sport. Finally, ‘Slightly Committed Runners’ show lower levels of enthusiasm, training frequency, experience and institutional ties to running. Ref. [12] studied segmentation based on commitment, loyalty and subjective well-being, identifying four groups in this case. The Moderate Group exhibits intermediate levels of commitment, loyalty and well-being, and represents a balanced relationship with running. The Low Group comprises participants with the lowest levels across all three dimensions. The Moderate–Low Group combines moderate levels of engagement and well-being with high behavioural loyalty and frequent participation in races. Finally, the High Group consists of runners with high levels of engagement and subjective well-being, for whom running plays a central role in their lifestyle.

In the field of competitive sport, ref. [81] identified three profiles: the Low Group, the Moderate Group and the High Group. The first is characterised by moderate levels of autonomous motivation and low levels of controlled motivation and amotivation. The Moderate Group exhibits intermediate or high levels of autonomous motivation, alongside moderate levels of controlled motivation. The High Group combines high levels of autonomous and controlled motivation with low levels of amotivation. Although this latter profile is associated with better performance outcomes, it may also be linked to higher levels of emotional and physical exhaustion, demonstrating that intense motivation does not always lead to greater well-being.

More recent research has expanded these models by incorporating emerging dimensions, such as inclusion and digital interaction. [13], in their study of the Magaluf Half Marathon, identified five profiles. ‘Digital Enthusiasts’ combine high levels of digital interaction with high levels of hedonism and inclusion, as well as a moderate-to-high valuation of personal challenge. ‘Inclusive Enjoyers’ are characterised by high levels of hedonism, inclusion and socialisation, although they show a low orientation towards competition. “Socialisers” place particular importance on shared enjoyment and social interaction, whilst inclusion, personal challenge and digital interaction carry less weight. “Hedonic Achievers” combine enjoyment of the experience with a strong interest in personal challenge and individual improvement. Finally, “Inclusivists” attach the greatest relative importance to inclusion and show a lower orientation towards competition, socialisation and digital interaction.

In line with these emerging new dimensions, ref. [14] found that incorporating inclusion into the model enabled them to identify six profiles. ‘Individual Challenge Seekers’ show a marked orientation towards hedonism and self-improvement, with less interest in socialisation and digital interaction. ‘Inclusive Social Hedonists’ combine high levels of inclusion, hedonism and socialisation, but exhibit low competitive motivation. ‘Digital Social Achievers’ constitute a profile characterised by high overall engagement, with high scores in inclusiveness, hedonism, socialising, digital interaction and personal challenge. For their part, ‘Moderately Inclusive All-Rounders’ show moderate and balanced scores across all dimensions, without any clearly dominant motivation. ‘Inclusive Individual Hedonists’ combine high levels of inclusiveness and hedonism with a lower orientation towards socialisation and digital interaction. Finally, ‘Inclusive Social Competitors’ have high scores for inclusiveness, hedonism, socialisation and personal challenge, but low motivation relating to digital interaction.

From a more psychological perspective, ref. [82] identified three profiles based on the relationship between motivation and self-efficacy. “Internally Motivated Athletes” display high self-efficacy and high levels of intrinsic motivation, linked to learning, self-improvement and enjoyment of the activity. “Externally Motivated Athletes” show lower self-efficacy and a greater reliance on external rewards, pressures or regulations. Finally, “Highly Motivated Athletes” score highly on both intrinsic and extrinsic motivation, accompanied by a high perception of self-efficacy.

3. Methodology

3.1. Survey Design

The questionnaire was informed by previous studies of motivation in running events, and its items were adapted to the specific context of the Neapolis Marathon [13,14,83]. Before distribution, the draft was reviewed by the event organizer for wording and relevance to the event. The questionnaire was available in Italian and English and comprised two sections. The first included 20 motivational items, rated on a seven-point Likert scale (Table 1); the second collected categorical sociodemographic information. The measurement structure and psychometric properties of the instrument were subsequently examined using the data collected in the present study.

Table 1. Motivation items.

Code	Item	References
M01 M02 M03 M04	I enjoy practising this sport. I compete to keep myself physically fit. I compete because I feel it helps me stay healthy. The emotions it evokes in me.	[13,34,84]
M05 M06 M07	The competition is the best part of taking part in this event. I give it my all when practising my favourite sport. The more competitive it is, the more I enjoy taking part in this event.	[21,46,50,85]
M08 M09 M10 M11	I’m really looking forward to the side events that accompany the main event. I’m keen to experience the scenery and setting of Naples. I hope to enjoy other outdoor activities during my stay. Naples’ appeal offers an unrivalled destination experience.	[17,86,87,88]
M12 M13 M14 M15 M16	It gives me the chance to spend time with friends. There’s a real sense of camaraderie amongst the people I’m competing against. I feel a bond with the people competing alongside me. Taking part as part of a group leads to better social relationships. I enjoy taking part because it gives me the chance to meet people.	[21,26,34,87]
M17 M18 M19 M20	It is special that the event is gender-inclusive. It is special that the event is inclusive of people of all ages. It is important that the event is inclusive of people with disabilities. It is important that it is an internationally, ethnically and culturally diverse event.	[14,20,86]

When designing the questionnaire, priority was given to the clarity of the statements and the conciseness of their format, with the aim of reducing the mental effort required and preventing fatigue amongst the athletes surveyed [89]. These methodological decisions were fundamental to guaranteeing the quality and consistency of the information obtained, whilst minimising potential errors during the data collection phase [90].

3.2. Sampling and Data Collection

The 2025 Neapolis Marathon was held on 19 October 2025. Data were collected during the following week, from 20 to 26 October 2025. The event organiser emailed a link to the online questionnaire to all 5500 registered participants. Participation was voluntary and anonymous. A total of 791 valid responses were obtained, corresponding to a response rate of 14.38%.

3.3. Data Analysis

To examine the responses and assess the set objectives, Exploratory Factor Analysis was conducted using IBM SPSS Statistics v28. Confirmatory Factor Analysis was performed using JASP 0.98.21.0, with the robust maximum likelihood (MLR) estimator. The hierarchical Ward procedure and subsequent k-means clustering were conducted using IBM SPSS Statistics v28. The reliability of the various sections of the questionnaire was tested using Cronbach’s alpha [91], with values in all cases exceeding the threshold of 0.70 recommended in the literature [92]. Prior to the factor analysis, the distribution of the Likert-scale items was analysed to verify their normality using the Kolmogorov–Smirnov test [93,94]. The results indicated a lack of normality (p < 0.05), which justified the use of non-parametric methods in the analyses complementing the factor model.

3.3.1. RQ1. Motivational Structure

To address RQ1, an exploratory factor analysis (EFA) was conducted in IBM SPSS Statistics v28 using principal component analysis (PCA) as the extraction method and Varimax rotation. The exploratory analysis was used to examine the dimensionality of the motivation items and identify behavioural patterns [95]. The sample size was considered adequate because it exceeded 300 cases and met the recommended minimum case-to-item ratio [92,96]. Sampling adequacy was assessed using the Kaiser–Meyer–Olkin index, with values above 0.70 considered acceptable [97], and factorability was examined using Bartlett’s test of sphericity [98]. Components with eigenvalues greater than 1 were retained [99]. Each retained component was required to contain at least three items with loadings above 0.40 [100], and the solution was expected to explain at least 50% of the total variance [101]. Items that did not meet these criteria were removed iteratively; Cronbach’s alpha and the component structure were then recalculated. PCA procedures were reported with reference to recommendations for sports science research [102]. The resulting measurement structure was subsequently assessed using CFA in JASP with the MLR estimator.

At a later stage, Confirmatory Factor Analyses (CFA) were carried out using the robust maximum likelihood (MLR) procedure, due to the ordinal nature of the indicators used. In order to verify the quality of the model’s fit to the data, validation criteria were set at values greater than 0.90 for the CFI and TLI indices [103]. Furthermore, an RMSEA < 0.08 was used as an indicator of the model’s simplicity or parsimony [104] and an SRMR < 0.08 as a measure of residual error [102]. The comparison between the different models was based on increases in the CFI and TLI indices, alongside decreases in the RMSEA and SRMR values. This methodology follows the recommendations for incremental improvement of model fit proposed by experts in structural equation modelling [103,105], enabling us to confirm whether the motivations analyzed constitute a well-defined framework.

3.3.2. RQ2. Segmentation of Participants

To address Research Question 2, a two-phase cluster analysis was conducted to segment the sample into groups with similar internal characteristics, based on the responses to the Likert scale. This technique is well-supported by research in the fields of sports and tourism management [106]. In the initial phase, Ward’s hierarchical method was applied to minimize variance within clusters and obtain a preliminary estimate of the optimal number of segments [107]. This decision was based on an examination of the agglomeration history and the observation of significant jumps in the coefficients [108]. In the second phase, the solution obtained was refined using the k-means algorithm, a non-hierarchical method that iteratively re-groups cases until the greatest possible homogeneity is achieved in the final partition [109]. Finally, the resulting groups were characterized according to their socio-demographic profile and internal characteristics, with each group being assigned a name representative of its main attributes.

4. Results

The average participant in the 2025 Neapolis Marathon is a man aged between 31 and 50, with a university education and currently in employment. Table 2 presents a detailed overview of the sociodemographic characteristics of the participants included in the sample.

Table 2. Sociodemographic profile of the sample.

Variable	Category	n	%
Gender	Male Female	590 201	74.6% 25.4%
Age	18 to 30 years old 31 to 50 years old More than 50 years old	100 390 301	12.6% 49.3% 38.1%
University graduate	Yes No	484 307	61.2% 38.8%
Occupation	Employed Any other situation	695 96	87.9% 12.1%

Table 3 shows the descriptive statistics for the items comprising the motivation scale. Enjoyment and health items received the highest means, while competition-related ratings were more varied.

Table 3. Descriptive statistics of the sample.

Items	Mean	Standard Error	Standard Deviation
M01 M02 M03 M04	6.63 6.32 6.41 6.54	0.028 0.037 0.034 0.030	0.789 1.032 0.970 0.830
M05 M06 M07	4.67 5.84 4.33	0.063 0.045 0.069	1.778 1.278 1.951
M08 M09 M10 M11	4.77 6.16 5.78 5.99	0.061 0.043 0.054 0.046	1.718 1.199 1.519 1.290
M12 M13 M14 M15 M16	5.55 4.84 5.45 5.79 5.14	0.061 0.071 0.055 0.051 0.063	1.722 1.993 1.539 1.438 1.775
M17 M18 M19 M20	5.50 6.09 6.23 6.14	0.063 0.050 0.046 0.049	1.770 1.392 1.304 1.386

4.1. Analysis of the Motivational Structure (RQ1)

An analysis of the rotated component matrix was carried out, confirming that each identified factor included at least three items, and that all items with factor loadings greater than 0.400 were exclusively associated with a single component, thereby ensuring the conceptual coherence of the resulting dimensions. However, a more detailed examination of the factor loadings revealed that item M08 did not meet the established fit criteria nor reach the minimum required factor loading threshold. Consequently, this item was removed from the analysis in order to maintain the intended methodological rigour. Following this refinement process, the final scale comprised 19 items.

The EFA yielded the following results: Chi-square = 7371.553, p < 0.05; KMO = 0.842. This finding confirms the presence of an underlying factor structure, thereby validating the use of EFA as an analytical technique [110]. In terms of representativeness, the model accounted for 68.158% of the total variance, indicating a robust explanatory capacity of the proposed model. Specifically, the inclusion dimension emerged as the factor with the greatest explanatory power, followed hierarchically by the dimensions of socialisation, sporting hedonism, destination appeal and competition. Finally, the reliability of the identified constructs was considered optimal, given the high scores obtained for both Cronbach’s alpha and McDonald’s omega, indicators that attest to the internal consistency of the scales. The detailed parameters derived from this procedure are summarised in Table 4.

Table 4. Results of the Exploratory Factor Analysis.

Item	INC	SOC	HED	DES	COM	Eig. 1	Exp. Var. 2	α 3	ω 4
M20	0.851					3.258	17.149%	0.890	0.892
M18	0.848
M19	0.820
M17	0.803
M14		0.788				2.851	15.007%	0.810	0.809
M15		0.780
M13		0.695
M12		0.668
M16		0.632
M03			0.828			2.588	13.620%	0.778	0.749
M02			0.783
M01			0.684
M04			0.659
M09				0.849		2.145	11.290%	0.778	0.783
M10				0.800
M11				0.748
M07					0.905	2.108	11.092%	0.802	0.853
M05					0.899
M06					0.597
(5)	0.842
(6)	7371.553
(7)	171
(8)	0.000
(9)	6
(10)	68.158%

Notes: ¹ Eigenvalues, ² Individual explained variance for each factor, ³ Cronbach’s Alpha (α), ⁴ McDonald’s Omega (ω), (5): Kaiser–Meyer–Olkin (KMO), (6): Chi-Square, (7): degrees of freedom, (8): p-value, (9): number of iterations; (10) total explained variance.

The first factor component (INC) is linked to a motivational dimension based on the inclusive nature of the sporting event. This factor comprises the following items: M20 (It is a particular motivation that the event is an internationally diverse event in terms of ethnicity and culture), M18 (It is a particular motivation that the event is inclusive of people of all ages), M19 (It is a special motivation that the event is inclusive of people with functional diversity) and, finally, M17 (It is a special motivation that the event is inclusive from a gender perspective). The convergence of these items accounts for 17.149% of the total variance inherent in the motivational items of the runners participating in the 2025 Neapolis Marathon. In line with the principles of equity and diversity that define the competition, this latent structure has been designated as the ‘inclusion dimension’.

The second factor (SOC) is associated with a motivational aspect focused on interpersonal interactions and bonds, developed both during the course of the sporting event and upon its conclusion. The items comprising this dimension are M14 (I feel a bond with the people competing alongside me), M15 (Participating as part of a group leads to better social relationships), M13 (There is a sense of camaraderie amongst the people I compete with), M12 (I enjoy taking part because it gives me the chance to spend time with friends) and, finally, M16 (I enjoy taking part because it gives me the chance to meet new people). Taken together, this group of variables explains 15.007% of the model’s total variance. Given the nature of the indicators that make it up, this latent structure has been termed the ‘socialisation dimension’.

The third factor component (HED) is associated with a motivational dimension based on the enjoyment and personal satisfaction derived from attending the competition. This structure comprises items M03 (I compete because I feel it helps me stay healthy), M02 (I compete to keep myself physically fit), M01 (The pleasure I get from practising this sport.) and M04 (The emotions it evokes in me). Taken together, this cluster of items accounts for 13.620% of the total variance in the model. Given its focus on enjoying the experience and the surroundings, this dimension has been categorised as the “sporting hedonism dimension”.

The fourth factor (DES) is linked to a motivational dimension based on an interest in undertaking tourist activities complementary to the competition, prompted by the trip to Naples. This structure comprises items M09 (I am looking forward to experiencing the scenery and setting that Naples has to offer), M10 (I hope to enjoy other outdoor activities during my stay in Naples) and M11 (“The appeal of Naples offers an unrivalled destination experience”).

Taken together, this group of items explains 11.290% of the total variance in the model, which highlights the importance participants attach to the city’s tourist appeal and the activities it offers. Consequently, this analytical construct has been termed the ‘destination appeal dimension’.

The fifth and final factor (COM) is associated with a motivational dimension linked to competitive spirit, both in relation to personal performance and in comparison with other runners. This component comprises the items M07 (The greater the competition, the more I enjoy taking part in this event), M05 (Competition is the best part of taking part in this event.) and M06 (‘I give it my all when practising my favourite sport’). This factor accounts for 11.092% of the total variance and has been termed the ‘competitive dimension’.

Table 5 sets out the results derived from the Confirmatory Factor Analysis (CFA). The proposed structure demonstrated a satisfactory level of fit with respect to the empirical data collected, as evidenced by the following fit indices: χ²(142) = 1133.696; p < 0.001; CFI = 0.949; TLI = 0.939; RMSEA = 0.094; 90% CI [0.089; 0.099]; and SRMR = 0.069. Furthermore, all standardised factor loadings proved to be statistically significant, exceeding the required minimum thresholds by falling within a range of 0.663 to 0.960. This result indicates an appropriate relationship between the items analysed and their corresponding latent constructs. Similarly, the composite reliability coefficients (CR) exceeded the threshold of 0.70 for all factors assessed, with scores ranging from 0.856 to 0.939. At the same time, the average variance extracted (AVE) was above the established benchmark of 0.50 across all dimensions, with values ranging from 0.582 to 0.794. The convergence of these metric indicators confirms the validity of the proposed measurement model.

Table 5. Results of the Confirmatory Factor Analysis.

Factors	Items	SFL 1	AVE 2	CR 3
Inclusion	M20	0.935	0.794	0.939
	M18	0.881
	M19	0.930
	M17	0.826
Socialisation	M14	0.947	0.582	0.872
	M15	0.944
	M13	0.960
	M12	0.752
	M16	0.754
Sporting hedonism	M03	0.844	0.711	0.908
	M02	0.784
	M01	0.785
	M04	0.666
Destination appeal	M09	0.770	0.666	0.856
	M10	0.803
	M11	0.817
Competitive	M07	0.663	0.731	0.891
	M05	0.872
	M06	0.912
χ2(df 4)		1133.696 (142)
p-value		<0.001
CFI 5		0.949
TLI 6		0.939
RMSEA 7 [CI 8 90%]		0.094 [0.089; 0.099]
SRMR 9		0.069

Notes: ¹ = Standardized factor loadings; ² = Average variance extracted; ³ = Composite reliability; ⁴ = Degrees of freedom; ⁵ = Comparative Fit Index; ⁶ = Tucker–Lewis Index; ⁷ = Root mean square error of approximation; ⁸ = Confidence interval; ⁹ = Standardized root mean square residual.

To test the discriminant validity of the proposed model, the Heterotrait–Monotrait (HTMT) ratio was applied; the resulting parameters are summarised in Table 6. In all the measurements carried out, the calculated coefficients were below the recommended critical threshold of 0.85. This empirical finding provides the statistical evidence required to confirm that the five latent constructs under study are clearly distinguishable from one another. Consequently, the findings derived from the Confirmatory Factor Analysis corroborate the existence of a multidimensional motivational structure.

Table 6. Heterotrait–monotrait ratio.

Variables	INC	SOC	HED	TUR	COM
INC	1.000
SOC	0.536	1.000
HED	0.409	0.412	1.000
TUR	0.402	0.496	0.420	1.000
COM	0.191	0.335	0.500	0.253	1.000

4.2. Segmentation of Participants (RQ2)

Furthermore, in the hierarchical cluster analysis, the dendrogram and agglomeration history were examined, revealing a notable increase in the agglomeration coefficient when moving from a solution with three clusters to one with two. This behaviour justified the selection of a solution comprising three groups.

A segmentation analysis was carried out based on the five previously validated motivational dimensions (inclusion, socialisation, sporting hedonism, destination appeal and competition), which were standardised using Z-scores.

The hierarchical cluster analysis, applied using Ward’s method, revealed a well-defined clustering structure of the cases. Examination of the agglomeration history revealed a significant increase in the agglomeration coefficient when moving from a three-cluster solution to a two-cluster solution (from 3057.564 to 3950.000), which was more pronounced than that recorded in the previous merger from four to three clusters (from 2647.417 to 3057.564). This pattern provided solid empirical support for the choice of a solution comprising three clusters.

Subsequently, a non-hierarchical cluster analysis was carried out using the k-means algorithm, which converged after 13 iterations. This statistical procedure enabled the identification of three population segments characterised by high intra-group homogeneity and significant inter-group heterogeneity, with no hierarchical dependency structure observed between them. The results reveal statistically significant differences between the resulting clusters. Table 7 presents a detailed breakdown of the participants’ distribution in relation to the previously identified motivational dimensions. It also sets out the descriptive statistics—mean (M) and standard deviation (SD)—for each factor, broken down for each of the three clusters analysed.

Table 7. Characterization of each cluster.

Variables	Cluster 1 = Inclusive Experimenters			Cluster 2 = Hedonists			Cluster 3 = Enthusiasts
	n = 210 (26.6%)			n = 77 (9.7%)			n = 504 (63.7%)
	Z	M	SD	Z	M	SD	Z	M	SD
INC	−0.068	5.90	0.92	−2.162	3.23	1.29	0.359	6.45	0.76
SOC	−0.443	4.78	1.17	−1.428	3.52	1.24	0.403	5.87	0.93
HED	−0.915	5.83	0.72	−0.700	5.98	0.93	0.488	6.82	0.33
TUR	−0.445	5.48	1.12	−1.155	4.69	1.38	0.362	6.38	0.79
COM	−0.914	3.63	1.21	−0.224	4.62	1.32	0.415	5.54	1.13
Gender (V = 0.072; p = 0.129)
Male	n = 148 (70.5%)			n = 63 (81.8%)			n = 379 (75.2%)
Female	n = 62 (29.5%)			n = 14 (18.2%)			n = 125 (24.8%)
Age (V = 0.091; p = 0.011)
18 to 30 years old	n = 33 (15.7%)			n = 13 (16.9%)			n = 54 (10.7%)
31 to 50 years old	n = 100 (47.6%)			n = 47 (61.0%)			n = 243 (48.2%)
More than 50 years old	n = 77 (36.7%)			n = 17 (22.1%)			n = 207 (41.1%)
Educational level (V = 0.094; p = 0.031)
University degree	n = 141 (67.1%)			n = 52 (67.5%)			n = 291 (57.7%)
Any other situation	n = 69 (32.9%)			n = 25 (32.5%)			n = 213 (42.3%)
Occupation (V = 0.023; p = 0.805)
Employed	n = 184 (87.6%)			n = 66 (85.7%)			n = 445 (88.3%)
Any other situation	n = 26 (12.4%)			n = 11 (14.3%)			n = 59 (11.7%)

Finally, the analysis of the socio-demographic profile of the clusters, carried out using contingency tables, did not reveal any statistically significant associations between group membership and certain socio-demographic variables, such as gender (χ²(2) = 4.096, p = 0.129; V = 0.072) or occupation (χ²(2) = 0.433, p = 0.805; V = 0.023). However, statistically significant associations were identified with age (χ²(4) = 13.015, p = 0.011), with a small effect size (Cramer’s V = 0.091); and with educational attainment, distinguishing between graduates and non-graduates (χ²(2) = 6.967, p = 0.031), where a small effect size was also observed (Cramer’s V = 0.094).

Cluster 1, termed ‘Inclusive Experiencers’, comprises 26.6% of participants and is characterised by high scores on dimensions related to the in-person experience of the event, such as hedonism and the attractiveness of the destination, as well as high scores on the inclusivity dimension. This segment has the highest proportion of women of the three. Cluster 2, identified as “Hedonists”, comprises 9.7% of participants and is distinguished by particularly high scores on the sporting hedonism factor. This segment shows the greatest gender disparity among the clusters, with a male majority. Cluster 3, termed “Enthusiasts”, is distinguished by having the highest scores across all dimensions.

5. Discussion

The motivational framework identified in the Neapolis Marathon 2025 supports the multidimensional nature of participation in endurance events. The model integrates traditional dimensions, such as hedonism, socialisation and competition, alongside emerging factors related to inclusion and the appeal of the destination. It also confirms that hedonism is a key element in sporting engagement, which supports the theory of engagement in [37]. This importance of intrinsic pleasure is consistent with previous studies that identify personal enjoyment and psychological achievements as the most valued motivational factors amongst runners [11]. Furthermore, the sustained presence of this motivation in the sample supports the hypothesis that enjoyment and well-being are fundamental factors in ensuring that sporting activity is maintained throughout adulthood [34,44].

With regard to the competitive dimension, it has been found that personal challenge and self-improvement remain essential driving forces, as suggested by [46]. The observed desire to improve individual performance aligns with the idea that the perception of competition is key to the formation of a strong athletic identity [49,50]. Furthermore, the integration of personal goals across various career trajectories corroborates contemporary findings in which personal challenge emerges as a central dimension that transcends mere external comparison [13,14,21,59].

Inclusion was the dimension with the greatest explanatory power in the factor model. This result supports arguments proposing the incorporation of inclusion as a specific motivational factor within the study of career events [20,21]. The positive assessment of an inclusive environment is consistent with the literature, which indicates that this factor strengthens community cohesion and enhances loyalty towards the event [62,70]. Similarly, the international nature of the race confirms that mass events currently act as catalysts for socio-cultural and functional diversity [30]. The results from the Neapolis Marathon are partially consistent with the findings of [21,68]. In both studies, women attached greater importance to inclusion, equality, social integration and recognition within the sporting community, whilst men placed greater value on perceived equality during the competition. In Naples, the ‘Inclusive Experiencers’ cluster, characterised by high scores for inclusion, hedonism and destination appeal, had the highest relative proportion of women, suggesting that women may have a relatively greater presence in inclusion-oriented profiles.

The identified components of socialisation and social affiliation are confirmed as fundamental psychological needs that the event helps to fulfil [30]. The atmosphere of camaraderie and the connection with other runners are consistent with the view of long-distance running as ‘modern rituals’ that foster positive emotions and social capital [111,112]. This need for a sense of belonging, which is common to all participants, is consistent with the literature that identifies socialisation as an essential integrative dimension in the current sporting landscape [36].

With regard to tourism motivation, the interest in the landscape and the city’s urban setting confirms that the environment is a critical determinant of enjoyment of sporting leisure [74]. The observed search for immersive experiences at the destination supports the notion that marathon tourism allows athletes to escape their routines and seek psychological wellbeing [3,10]. This synergy between sport and destination reinforces the restorative value of the experience, as has been proposed in studies on road events [76].

Finally, the segmentation identified in the Neapolis Marathon 2025 confirms the intrinsic heterogeneity of the participants, validating the need for this analytical approach to understand differences in motivational structures [11,12]. The emergence of three distinct groups is consistent with the trend in the literature, which typically reports between three and five clusters [13]. Cluster 1 (“Inclusive Experiencers”) stands out for incorporating emerging dimensions such as inclusion and the appeal of the destination. This finding supports the proposal by [13] regarding the need to identify profiles that link motivation with tourism engagement in destinations. This cluster resembles the ‘Inclusive Individual Hedonists’ identified by [14] or the ‘Inclusive Enjoyers’ of [13], who also scored highly on hedonism and inclusion.

For its part, Cluster 2 (“Hedonists”), characterised by the intrinsic pleasure derived from the activity and a male-dominated group, resembles the “individualistic hedonists” identified by [11], the ‘Hedonic Recreational Runners’ identified by [14], and the ‘Hedonic Achievers’ described by [13]; all these groups are characterised by the significant importance they attach to the hedonic dimension. Finally, Cluster 3 (“Enthusiasts”), with high scores across all dimensions, constitutes the group most closely resembling the Enthusiasts described by [11]. It also bears a close resemblance to the “highly motivated” or “highly engaged” profiles described by [12]. Similarly, it shares the pattern of high overall motivation seen in the ‘Highly Motivated Athletes’ identified by [82], the ‘High Group’ described by [81], and the highly committed runners identified by [80]. This third cluster of ‘Enthusiasts’ contrasts with the ‘Moderately Inclusive All-Rounders’ identified by [14] and the moderate groups described by [12], characterised by moderate scores across all dimensions.

6. Conclusions

6.1. Theoretical Conclusions

This study contributes to the scientific literature by confirming the multidimensional nature of motivation in the context of endurance running. The findings validate the integration of classical constructs derived from frameworks such as the push/pull factor theory. Furthermore, the research adds theoretical value by confirming that inclusion constitutes a primary motivational dimension, thereby expanding traditional models of sporting segmentation and offering a more holistic view of athlete behaviour at mass events.

6.2. Empirical Conclusions

This study provides a 19-item instrument with initial evidence of reliability and structural validity for measuring motivation at major running events, consolidating key dimensions such as hedonism, competition, socialisation, inclusion and destination appeal. The research identifies three clearly differentiated motivational segments that enable the diversity of participants in the 2025 Neapolis Marathon to be mapped. These findings confirm the metrical robustness of the proposed model and demonstrate its usefulness in capturing the heterogeneity of the contemporary sporting experience in urban and international contexts.

6.3. Practical Implications

The segmentation obtained provides a strategic roadmap for event organisers and destination managers to design tailored initiatives based on athletes’ motivational profiles. For ‘inclusive experiencers’—given that this group, which has a high proportion of women, values inclusion and the appeal of the destination—it is recommended to promote ‘parallel tourism’ programmes that include side events, such as guided cultural tours. Reinforcing messages of diversity and accessibility in official communications will increase this segment’s loyalty to the event brand.

For ‘hedonists’—a group motivated by the intrinsic pleasure of running and with a high proportion of male participants—strategies should focus on the sensory experience of the race. Improving services along the route (music, specific cheering points) and offering high-quality audiovisual content about the course will satisfy their quest for emotional gratification. Finally, for the ‘enthusiasts’—who demonstrate the highest levels of engagement across all areas—this cluster is the ideal candidate for loyalty programmes and brand ambassadors. Offering premium services, such as technical recovery zones or performance-focused information sessions, would align competitive expectations with the overall experience.

6.4. Limitations

Despite the contributions of this study, certain limitations must be acknowledged. Firstly, the use of non-probability sampling and a cross-sectional design limit the generalisability of the results to other contexts or time periods. Furthermore, the study focuses on a single event, the 2025 Neapolis Marathon, which could introduce biases linked to the specific profile of its participants. From an instrument perspective, although key dimensions have been validated, the instrument may not capture environmental motivations or a desire to connect with nature, which are characteristic of other types of race.

6.5. Future Research Directions

It would be of great interest to replicate this study in other cultural contexts and on international routes to test the stability of the identified clusters. From a methodological perspective, future research could employ structural equation modelling (PLS-SEM) or artificial intelligence techniques, such as artificial neural networks (ANN), to model the causal relationships between motivations and economic impact or loyalty to the tourist destination with greater precision. Finally, analysing the long-term effect of the race on the city’s brand image would provide a deeper insight into the sport-tourism nexus.