Identifying Brand Association Patterns Across the Psychological Continuum Model Stages: The Case of Winter Sports

Abstract

The positive economic, social, and environmental influences of the active sport tourism market are well documented today. This study aimed to map brand association patterns across the different stages of the Psychological Continuum Model (PCM) within the context of winter skiing. The PCM was used as the theoretical framework to categorize participants into stages according to their skiing involvement levels. The data was collected from recreational skiers at two major ski resorts in Greece. Participants were classified into the PCM stages. The findings revealed that associations with the activity significantly discriminated against PCM stages. Product delivery associations were salient only at the Attraction stage, indicating the importance of functional evaluations for novice participants. In contrast, tradition and peer acceptance associations consistently predicted membership across all stages, highlighting their enduring symbolic and social relevance. Escape-related associations were diminished in higher commitment levels, whereas importance and affective associations emerged as key predictors in the Attachment and Allegiance stages. The study extends the PCM by integrating brand association theory in the context of sport tourism and offers practical implications for stage-specific branding strategies in participatory sports services.

1. Introduction

In a global 564.7 $ billion sport tourism market, it has been reported that active sport tourism (participation in outdoor activities) creates a global economic activity of 231.53 billion (IMARC Group, 2024). By definition, the active sport tourism market is an alternative form of tourism that respects the physical environment and involves local communities in the design and delivery of services (Hinch et al., 2018); it therefore has the perspective to address several of the Sustainable Development Goals (SDGs), such as SDG 3: “ensure healthy lives and promote well-being for all at all ages”; SDG 16: “promote peaceful and inclusive societies”; SDG 12 “ensure sustainable consumption and production patterns”; SDG 13 “take urgent action to combat climate change and its impacts”; and SDG 15 “protect, restore and promote sustainable use of terrestrial ecosystem and halt biodiversity loss” (United Nations, 2024).

Moving towards a service experience economy (Agapito & Sigala, 2024), active sports tourism provides an ideal context for service co-creation ( John & Supramaniam, 2026), in which participants expect creative interaction with service providers and local communities, which will lead to the formation of positive cognitive and affective experiences. In a detailed review of the customer experience literature, Agapito and Sigala (2024) categorized the drivers of customer experiences in internal (socio-demographics, psychographics, and culture) and external (brand-related stimuli), which are built to touch points in relation to brand attributes such as atmospherics, the social environment, social interactions, etc.

It has been proposed that the objective of experience design (as part of experience management) is to develop a connection between users (tourists), design elements, and the contexts of interactions (Agapito, 2020). To capture these connections, the present study introduces the concept of activity associations, examining whether distinct patterns of associations emerge among individuals situated at different stages of the PCM within the context of active sport tourism (mountain skiers). In sport and leisure settings, such associations extend beyond functional value and encompass symbolic, experiential, and identity-related dimensions (Gladden & Funk, 2001, 2002; Kunkel et al., 2014, 2016; Lianopoulos et al., 2025). Building on Alexandris’s (2016) work on activity (skiing) brand personality, we argue that recreational activities can also possess distinct personality profiles and can therefore be conceptualized as specific brands (e.g., skiing, football), like the way sport clubs and athletes exhibit unique personalities and brand identities (Alexandris, 2016). To operationalize activity associations, we draw on brand theory and the definition of brand associations as the cognitive and affective links individuals form with a particular brand (Aaker, 1996; K. Keller, 2008). Recent evidence by Karagiorgos et al. (2023) further supports this approach, demonstrating that activity (hiking) associations—related to tangible and intangible attributes, perceived benefits, and attitudinal elements—can predict attachment and participants’ loyalty.

Developing consumer loyalty has been one of the most popular topics in the marketing and management literature, since loyal customers are linked with company profitability (Gazi et al., 2024; Helgesen, 2006; Islam & Akagi, 2018). In the participatory sport literature, there have been several theoretical models to study how participants’ loyalty is developed and which are the factors that influence it. The Psychological Continuum Model (PCM) has been one of the most well-established ones (D. Funk et al., 2023). It explains how individuals vary across four levels to develop loyalty: Awareness, Attraction, Attachment, and Allegiance. This model has been applied in both spectator and sport contexts, offering a good theoretical foundation for studying the development of consumer loyalty (Beaton et al., 2011; D. Funk et al., 2023). Several internal elements to individual factors have been studied in relation to the PCM stages, such as motives, constraints, and perceived benefits, aiming to explain why and how sports participants are distributed across the stages of the model (Alexandris et al., 2017; Khodadadian et al., 2025; Lock et al., 2012); these internal factors reflect individual attitudes and perceptions. There have been no attempts so far to explicitly test brand-related aspects of the actual object in the context of participatory sports (e.g., sport activity), although there has been some evidence that brand personality attributes might differentiate across the stages of the model (Alexandris, 2016).

Although prior PCM research has examined how internal psychological factors—such as motives, constraints, and perceived benefits—differ among the stages of the model (Alexandris et al., 2017), only limited work has explored brand-related constructs, with studies focusing primarily on brand personality patterns in the different stages (Alexandris, 2016). What remains unknown is whether specific types of brand associations—functional, experiential, and symbolic—follow distinct patterns across PCM stages, particularly within participatory activity contexts. This study addresses that gap by introducing the concept of activity associations and empirically mapping their patterns across PCM stages using a multinomial staging approach in the context of winter skiing. Establishing how different activity brand association patterns are formed within the stages of the PMC can be useful for tourism and recreation practice. By identifying which associations matter most at each stage of psychological involvement, recreational practitioners, destination marketers, and policy makers gain a clearer foundation for segmenting participants more precisely, designing experience-based value propositions that align with brand association attributes, and shaping service environments that meet the expectations of active sport tourists.

2. Literature Review

2.1. Brand Associations in Sports and Leisure

Brand associations encompass the cognitive, emotional, and symbolic linkages that individuals form with brands (K. L. Keller, 2020). In leisure and sport contexts, these associations can shape consumer perceptions about a specific activity, and consequently, they can influence participation intention and loyalty (Karagiorgos et al., 2023, Lianopoulos et al., 2025). The conceptual roots of brand association stem from the broader marketing literature, particularly K. Keller’s (1993) model of brand knowledge, wherein it is proposed that associations are stored in the memory as nodes connected to the brand. Aaker’s (1996) framework similarly highlights the significance of strong, favorable, and unique brand associations in creating and sustaining brand equity. In recent years, there has been an attempt to apply brand association theory from commercial product branding (Dedeoğlu et al., 2019; K. L. Keller & Brexendorf, 2019; Liu & Chou, 2016) to more experiential domains such as sports and active leisure (D. Funk et al., 2023; Wear et al., 2018). This transition reflects a broader understanding of brands not merely as identifiers but also as experience-laden constructs, a trend catalyzed by the increasing commercialization of sport and recreational events (Tsuji & Schlueter, 2021; Yoshida & Gordon, 2012). Within this paradigm, brand associations are no longer solely derived from product performance but are co-constructed through consumption experiences, symbolic meaning, and community interactions (K. L. Keller, 2023).

The most used brand association framework was developed by Gladden and Funk (2001, 2002). This framework was grounded in three main pillars: Attributes, referring to descriptive features of a sports brand and that are divided into product-related (i.e., performance, team success, and coaching) and non-product-related attributes (i.e., logo, facilities, and tradition). These attributes serve as the foundational cues through which fans identify and differentiate teams. Benefits represent the values that fans derive from their association with the sports brand and are categorized as functional, experiential, and symbolic. Functional benefits relate to the quality and entertainment value of sports games. Experiential benefits involve emotional responses such as excitement and nostalgia derived from following the sports team. Symbolic benefits reflect Self-expression, social identification, and group belonging, allowing fans to reinforce their personal and social identities through team affiliation. Attitudes reflect the overall evaluation of the sports brand based on accumulated attributes and benefits. Factors such as knowledge of the brand, affective reactions, and importance might influence positive attitudes toward the sports team which, in turn, strengthen psychological commitment, loyalty behaviors, and engagement.

Emerging empirical research continues to validate the multifaceted nature of the brand association model. Specifically, Karagiorgos et al. (2023), in a recent study on mountain adventure destinations, developed a recreation-specific adaptation of Gladden and Funk’s (2002) Team Association Scale. Their findings reaffirmed the multidimensionality of brand associations in leisure settings by identifying dimensions such as tradition, escape, product delivery, and importance as significant contributors on place attachment. These findings align with a broader customer-based brand equity model (K. Keller, 1993), which emphasizes the psychological processes that mediate between experiential cues (e.g., event design, peer endorsement, and customer experience) and behavioral outcomes (Lianopoulos et al., 2025). For instance, Tsuji and Schlueter (2021) analyzed brand associations related to a sport event in Asia and found that variables such as product delivery, tradition, and brand knowledge shaped participants’ loyalty differently across consumer segments. Similarly, Ferreira et al. (2023) demonstrated that the perceived quality of event experience and emotional connection to place identity directly influence sport tourists’ brand-related behavior.

Recent literature has also paid attention to consumers’ role in generating brand meaning. The proliferation of social media, user-generated content, and peer networks has decentralized brand narrative construction (Andéhn et al., 2014; Popp & Woratschek, 2017). This evolution invites a re-conceptualization of brand association as a socially negotiated and dynamically evolving construct rather than a fixed marketing input. In the same way, Kunkel et al. (2013) confirmed that sports consumers articulate brand associations in nuanced ways by emphasizing not just performance or aesthetics but also emotional resonance, sense of community, and personal identity with professional sports. However, brand association research in participatory sports and especially in active leisure is still limited (Huang et al., 2015; Karagiorgos et al., 2023). Most of the sports studies have been focused on spectators (Ross, 2007; Wear & Heere, 2020), sports teams (Gladden & Funk, 2001, 2002), and sports leagues (Ross et al., 2007). Thus, to study the development of participants’ loyalty in the context of winter sports, in this study, PCM was used as the main theoretical framework.

2.2. The Psychological Continuum Model in Leisure

The Psychological Continuum Model (PCM), originally proposed by D. C. Funk and James (2001), offers a robust framework for understanding how individuals develop and deepen psychological connections within sport and leisure activities. This model integrates elements from consumer behavior, identity theory, and social psychology, providing a holistic account of sport-related involvement (D. Funk et al., 2023). In contrast to classic models of consumer behavior (Aaker, 1996; K. Keller, 1993), the PCM conceptualizes engagement as a dynamic, sequential process progressing through four hierarchical stages: Awareness, Attraction, Attachment, and Allegiance. At its core, the PCM posits that individuals traverse these stages as they internalize and personalize their connection to a sports object. Awareness involves basic recognition of a sports object with minimal knowledge and no emotional connection, often driven by media exposure or social influences; Attraction occurs when individuals develop interest based on perceived benefits such as entertainment or social interaction, leading to initial and situational engagement; Attachment reflects a deeper emotional and symbolic bond, where the sports object becomes part of an individual’s identity and guides consistent involvement; and Allegiance represents enduring loyalty and commitment, marked by persistent support and advocacy regardless of performance or external influences.

PCM has been applied across various leisure/sport contexts (Alexandris, 2016; Alexandris et al., 2017; Chung et al., 2022; Karagiorgos et al., 2025). Beaton et al. (2011) who used the model to operationalize and segment participants from an amateur rugby club and recreational skiers, reported significant differences in resistance to change and behavioral loyalty across the PCM stages. Similarly, Alexandris et al. (2017) employed the model in a study of recreational skiers and demonstrated that individuals at higher PCM stages were more likely to negotiate participation constraints effectively. The PCM was also examined in a recent study from Karagiorgos et al. (2025), in which the authors explored trail runners’ psychological commitment in relation to perceived wellbeing. The study reported that perceived wellbeing can significantly differentiate among runners into the stages. Studies have also extended the model into digital and virtual contexts. In a study of esports participants, Wang et al. (2025) demonstrated that psychological progression through the PCM stages was mirrored in online engagement patterns, fan identification, and consumption behavior by using digital innovativeness. Finally, Alexandris (2016) conducted the only study to date in which Aaker’s brand personality framework was examined in relation to the stages of the PCM in a participatory sport context. His findings showed that symbolic and trait-based perceptions of a sport activity—such as excitement, sophistication, or ruggedness—can differentiate levels of involvement, suggesting that activity-based brand meanings may play a role in how individuals progress through the PCM. However, this work focused exclusively on personality traits and did not examine broader categories of brand associations, such as functional, experiential, or symbolic benefits, nor did it test whether distinct association patterns emerge across PCM stages. We argue that a promising new direction for PCM research lies in integrating a brand association framework, as the pattern of brand associations is likely to differentiate across the stages of PCM. PCM theory suggests that individuals’ cognitive and affective structures evolve as they progress from lower to higher involvement stages (D. C. Funk & James, 2001). Research on brand associations similarly indicates that deeper involvement strengthens and differentiates the individual’s form with an activity (Gladden & Funk, 2001; K. Keller, 2008). Recent evidence in activity-based contexts further confirms that such associations intensify and become more identity-laden as commitment deepens (Karagiorgos et al., 2023). Taken together, these insights suggest that brand associations should not be uniform across PCM stages but instead follow distinct patterns as involvement increases. Based on this reasoning, the first hypothesis was formulated:

H1: 

Winter sport participants at different stages of the Psychological Continuum Model (Awareness, Attraction, Attachment, and Allegiance) will report significantly different levels of activity associations.

At the early stages of the Psychological Continuum Model, namely Awareness and Attraction, individuals tend to form more basic and concrete associations with an activity. These associations are often grounded in tangible or actively related elements—such as traditions, social norms, environmental cues, or peer influence—that help individuals recognize and initially engage with the activity. At these stages, meanings are largely functional, externally driven, and shaped by relatively simple cognitive structures. As individuals progress toward the Attachment and Allegiance stages, their psychological connection becomes more complex and internalized. The associations they form with the activity deepen and evolve into symbolic, emotional, and identity-based meanings. These may include expressions of self-identity, feelings of group belonging, personal importance, and the integration of the activity into one’s lifestyle or self-concept. This pattern reflects PCM’s central proposition that involvement develops through increasingly sophisticated cognitive and affective structures, ultimately leading to stronger, more enduring psychological commitment (D. C. Funk & James, 2001). In this way, the second hypothesis was set:

H2: 

The pattern of activity associations will differ across PCM stages, in the way that participants in higher PCM stages will report stronger emotional associations with the activity.

In conclusion, the Psychological Continuum Model remains a highly relevant and empirically validated framework for understanding engagement in leisure and sport contexts. Its integration with concepts such as activity brand associations can offer new ground for research, particularly in exploring the cognitive and affective mechanisms underpinning stage categorization.

3. Materials and Methods

The data were collected in February 2025, which is the peak of the winter tourism season in Greece. The study targeted Greek adult recreational skiers. A cross-sectional study design was employed, and participants were recruited using a convenience sampling method due to its feasibility and accessibility. It should be acknowledged that the cross-sectional design used in this study does not permit strong causal inferences. However, cross-sectional approaches remain well-established and widely employed in the social sciences as an appropriate means of examining theoretical models and identifying meaningful relationships among key constructs (Byrne, 2016; Hair et al., 2019). Data were obtained through an online questionnaire, which was distributed by the research team at two major ski resorts in northern Greece. Participants were invited to voluntarily participate in the study via a QR code. A total of 500 invitations were disseminated. A total of 302 valid questionnaires were returned, resulting in a response rate of 60.4%. Consent was received from all participants before filling out the questionnaires. The demographic analysis revealed that 62.6% (N = 189) were males and 37.4% (N = 113) were females. Their mean age was 32.6 years old. The age range was 20 to 66 (SD = 11.27, Median = 29, Q1 = 26, and Q3 = 36). Additionally, the mean age of each stage was Attraction = 29.8, Attachment = 31.6, and Allegiance = 34.8. Regarding educational attainment, the majority held undergraduate degrees (N = 146, 48.3%) or postgraduate qualifications (N = 77, 25.5%), with the remainder having completed technical/vocational training (N = 34, 11.3%) or secondary education (N = 45, 14.9%). In terms of ski experience, most individuals had more than 5 years (N = 156, 51.7%), followed by four years (N = 44, 14.6%), one year (N = 43, 14.2%), two years (N = 32, 10.6%), and three years (N = 27, 8.9%). Their average mean ski days per year were 8 daily trips at a ski resort. Activity associations were measured with the activity associations scale developed and tested by Karagiorgos et al. (2023) in the Greek population. Karagiorgos et al. (2023) developed the scale based on the TAM scale (Gladden & Funk, 2001, 2002), including nine dimensions, each one consisting of three items: product delivery (i.e., skiing is exciting), tradition (viewed as a well-known, long established leisure activity), escape (i.e., provided a chance to break away from everyday life), peer acceptance (i.e., gives a feeling of being recognized as a skier), nostalgia (i.e., evokes memories and past ski experiences), knowledge (i.e., reflects how much participants know about the activity), importance (i.e., captures the subjective beliefs an individual attaches to the activity), and affective reactions (i.e., mirroring the participant’s emotional state). As reported, Karagiorgos et al. (2023) followed the established methodological procedures for scale development, including qualitative pre-testing, item screening, exploratory and confirmatory factor analyses, reliability assessment, and discriminant validity checks. Their work provides a robust methodological foundation for measuring brand-related constructs in sport and leisure contexts. A similar modification in leisure context has been made by Karagiorgos et al. (2023) and was found to be reliable and valid.

Leisure involvement was assessed using the scale developed by Kyle et al. (2003, 2004), adapted to the ski participation context. This instrument included three dimensions, each one consisting of three items: Attraction, Centrality and Self-expression. This scale has been validated across multiple studies in sport and leisure contexts (Alexandris, 2016; Havitz & Mannell, 2005; Kyle et al., 2003). According to D. Funk et al. (2023) and Beaton et al. (2011), this scale is suitable for categorizing sport participants into the PCM stages via a three-step staging model, as elaborated in the next section. Responses for both research tools were recorded on a 7-point Likert scale ranging from 1 (totally disagree) to 7 (totally agree).

A confirmatory factor analysis (CFA) was initially conducted to evaluate the factorial validity of the latent constructs. Following this, ski participants were segmented into the distinct PCM stages: Attraction, Attachment, and Allegiance. The second phase of the study followed the operational procedure outlined by D. C. Funk and James (2001) and later refined by Beaton et al. (2011). Three involvement dimensions—Attraction (hedonic enjoyment), Centrality (lifestyle importance), and Self-expression (identity relevance)—were measured using validated Likert-scale items. As recommended by Beaton et al. (2011), the first step involved calculating mean scores for each dimension to generate an individual involvement profile, e.g., Participant 1: Attraction = 6.2, Centrality = 5.6, Self-expression = 5.2; and Participant 2: Attraction = 5.2, Centrality = 4.6, Self-expression = 4.1. In the second step, these mean scores were used to create a ranked involvement profile according to the recommended thresholds, validated from D. C. Funk and James (2001) and across the relevant literature (Alexandris et al., 2017; Beaton et al., 2011; D. Funk et al., 2023). Specifically, researchers (Beaton et al., 2011; D. Funk et al., 2023) set the initial thresholds as low (<4.49), medium (4.50–5.74), and high (>5.75) involvement levels. In that case, Participant 1 has a high-Attraction level, medium-Centrality level, and low-Self-expression level profile and Participant 2 has a medium-Attraction level, low-Centrality level, and low-Self-expression level profile. In the final step, by following the recommended pattern from Beaton et al. (2011, p. 133) we categorized Participant 1 in the Attachment stage and participant 2 in the Attraction stage. This procedure was done manually for all participants. Since all respondents were active participants, none fell within the initial Awareness stage. Finally, a multinomial logistic regression analysis was conducted to assess the significant contribution of brand associations toward the PCM stages.

4. Results

4.1. Measurement Model

Model validation was carried out through CFA. The model fit demonstrated acceptable fit indices: χ²(1429.33)/df(410) = 3.4, p = 0.001, CFI = 0.929, TLI = 0.913, RMSEA = 0.083, and SRMR = 0.055. Regarding reliability, Cronbach’s alpha coefficients ranged from 0.81 to 0.91, while Composite Reliability (CR) indices ranged from 0.83 to 0.92 (Bagozzi & Yi, 1988), both indicating acceptable internal consistency. Convergent validity was confirmed through (a) t-values ranging from 4.55 to 23.16, surpassing the minimum threshold (≥±1.96) (Byrne, 2016), and (b) Average Variance Extracted (AVE) values exceeding the 0.50 criterion (see

Table 1. Confirmatory factor analysis.

Factors	Loading	t-Value	Mean	a	CR	AVE
Skiing involvement
Attraction			5.58	0.91	0.92	0.84
Skiing is pleasurable	0.92	23.16 ***
Participating in skiing is one of the most enjoyable things that I do	0.87	20.19 ***
I really enjoy skiing	0.91	21.55 ***
Centrality			4.41	0.89	0.92	0.79
I enjoy discussing skiing with others	0.82	15.43 ***
Skiing plays a central role in my life	0.86	19.96 ***
I find a lot of my life is organized around skiing	0.86	17.65 ***
Self-expression			4.94	0.88	0.92	0.83
When I participate in skiing, I can really be myself	0.85	16.66 ***
You can tell a lot about a person by seeing them skiing	0.91	21.51 ***
When I participate in skiing, others see me the way I want them to see me	0.87	20.32 ***
Brand Associations
Product delivery			5.45	0.90	0.90	0.86
Skiing is exciting	0.84	14.12 ***
Skiing is entertaining	0.86	14.53 ***
Skiing is enjoyable	0.80	11.18 ***
Tradition			5.21	0.87	0.90	0.82
Ski has a long history	0.86	12.50 ***
Ski has rich stories to tell	0.84	11.65 ***
Ski has no history (R)	0.84	13.39 ***
Escape			5.35	0.84	0.89	0.80
Ski provides me a temporary escape from life’s problems	0.91	20.12 ***
Ski helps me forget my day-to-day problems	0.88	17.83 ***
Ski takes me away from life’s hassles	0.86	18.94 ***
Peer acceptance			5.43	0.87	0.88	0.74
I began skiing because of my friends	0.89	21.28 ***
It is important to ski with my friends	0.88	19.47 ***
I like to ski because my friends like to ski too	0.85	18.94 ***
Nostalgia			5.26	0.83	0.83	0.72
Thinking of skiing brings back good memories	0.79	09.50 ***
I have fond memories of skiing	0.73	04.55 ***
I have fond memories of skiing with friends	0.75	07.99 ***
Knowledge			4.46	0.89	0.87	0.76
I possess a great deal of knowledge about ski activity	0.91	20.78 ***
If I were to list everything I knew about ski, the list would be quite long	0.88	19.03 ***
Compared to other winter activities, I consider myself an expert about ski	0.85	13.84 ***
Importance			4.56	0.90	0.88	0.76
I consider ski activity to be personally important	0.89	21.12 ***
Being a skier is important for me	0.92	20.97 ***
Compared to how I feel about other winter activities, ski is still my favorite	0.86	13.74 ***
Affective reactions			5.13	0.85	0.90	0.80
Foolish…Wise	0.81	13.28 ***
Bad…Good	0.84	15.37 ***
Worthless…Beneficial	0.81	10.94 ***
Boring…Interesting	0.77	07.23 ***

Note: *** = p < 0.001.

) (Brown, 2015). Discriminant validity was evaluated using Fornell and Larcker’s (1981) method; the square roots of AVE for each latent variable exceeded inter-factor correlations (see

Table 2. Inter-correlation matrix.

Variables	Inter-Correlation Matrix
	1	2	3	4	5	6	7	8	9	10	11
1. Attraction	0.917
2. Centrality	0.689	0.891
3. Self-expression	0.601	0.803	0.913
4. Product delivery	0.445	0.299	0.323	0.922
5. Tradition	0.527	0.370	0.433	0.442	0.900
6. Escape	0.579	0.298	0.231	0.429	0.788	0.894
7. Peer acceptance	0.354	0.201	0.501	0.535	0.795	0.834	0.849
8. Nostalgia	0.301	0.287	0.398	0.576	0.738	0.841	0.676	0.828
9. Knowledge	0.523	0.278	0.421	0.673	0.822	0.829	0.679	0.800	0.855
10. Importance	0.532	0.432	0.324	0.723	0.743	0.802	0.748	0.776	0.801	0.877
11. Affective	0.347	0.265	0.478	0.776	0.709	0.766	0.779	0.788	0.823	0.745	0.894

Note: Square root of AVE values in diagonal boldface.

), confirming the distinctiveness of constructs. To assess potential multicollinearity among the independent variables, a Variance Inflation Factor (VIF) analysis was conducted in SPSS 25.0, following recommended procedures (Vittinghoff, 2013). The results indicated that product delivery (VIF = 2.20), tradition (VIF = 4.38), escape (VIF = 5.45), peer acceptance (VIF = 4.02), nostalgia (VIF = 5.66), knowledge (VIF = 4.60), importance (VIF = 5.81), and affective (VIF = 5.39) all fell well below the commonly accepted threshold of 10, suggesting that multicollinearity was not a concern in the model.

4.2. Multinomial Logistic Regression

Using Beaton et al.’s (2011) three-step segmentation approach, ski participants were classified into the Attraction (N = 57, 18.9%), Attachment (N = 112, 37.1%), and Allegiance (N = 133, 44%) stages based on their leisure involvement profiles (see

Table 3. Multinomial regression outcomes among the PCM stages.

	Attraction N = 57, 18.9% Cluster 3	Attachment N = 112, 37.1% Cluster 2	Allegiance N = 133, 44% Cluster 1
Product delivery	0.34 * (1.21–3.54)	0.10 (−4.87–1.12)	−0.15 (2.08–4.06)
Tradition	0.40 * (2.97–5.61)	0.37 * 1.25–2.09)	0.32 * (0.56–1.21)
Escape	0.26 * (6.18–7.99)	0.14 * (0.78–1.69)	−0.09 (−1.58–0.48)
Peer acceptance	0.33 * (1.09–1.96)	0.29 * (1.19–1.87)	0.26 * (2.45–3.23)
Nostalgia	0.12 (−6.92–0.71)	0.04 (−4.22–1.35)	0.07 (−3.96–1.84)
Knowledge	0.25 * (−2.12–−1.78)	0.14 * (1.65–2.56)	0.11 * (1.50–2.76)
Importance	−0.35 (−6.62–1.73)	0.12 * (0.55–1.88)	0.23 * (2.35–5.62)
Affective reactions	0.02 (−1.25–1.96)	0.12 * (0.71–1.06)	0.19 * (0.93–1.31)

Note: * = p < 0.05, Upper line = beta loadings, lower line = confidence intervals (lower level–upper level).

). A multinomial logistic regression analysis was conducted to assess the significant contribution of cluster membership between brand associations and the PCM stages (Hair et al., 2019). A stepwise likelihood-ratio procedure was used with entry criteria of p = 0.05. The model demonstrated a significant improvement over the intercept model (X²(24) = 135.33, AIC = 543.45, and p = 0.001), indicating that the predictors jointly contributed to explaining cluster membership. Also, the overall model accounted for a moderate proportion of variance in cluster membership (Pseudo R2-Nagelkerke criterion = 0.391), suggesting substantive exploratory power (Hair et al., 2019). The classification test revealed that 64.2% of cases were correctly classified in the model (Attraction = 56.3%, Attachment = 50.9%, and Allegiance = 76.7%). This finding indicates acceptable discriminatory ability among clusters. The classification accuracy for the Attachment stage (50.9%) suggests potential overlap with adjacent stages, consistent with its theoretical positioning as a transitional stage between initial attraction and enduring allegiance. The results indicated that different associations predicted group membership, supporting the first hypothesis of the study. In detail, at the Attraction stage, tradition emerged as the strongest predictor (β = 0.40), followed by product delivery (β = 0.34), peer acceptance (β = 0.33), escape (β = 0.26), and knowledge (β = 0.25). For the Attachment stage, tradition again showed the largest effect (β = 0.37), followed by peer acceptance (β = 0.29). More moderate but significant effects were observed for escape (β = 0.14), affective reactions (β = 0.12), knowledge (β = 0.14), and importance (β = 0.12). At the Allegiance stage, tradition remained the most influential predictor (β = 32), followed by peer acceptance (β = 0.26), importance (β = 0.23), affective reactions (β = 0.19), and knowledge (β = 0.11), but with smaller magnitudes. To further support the robustness of the results, we ran two more multinomial logistic regressions by changing the reference group (i.e., reference group Attachment and Allegiance). The direction and significance of key predictors remained consistent across models, indicating robustness of the multinomial regression results, since no significant changes were made, i.e., Attachment reference group: AIC = 542.13, p = 0.001; Allegiance reference group: AIC = 544.71, p = 0.001.

Across all PCM stages, tradition, peer acceptance, and knowledge consistently predicted stage membership. Escape was influential at the Attraction and Attachment stages but did not contribute at the Allegiance stage, suggesting diminishing relevance in the commitment phase. Similarly, affective reactions and importance became salient only at the more advanced stages of Attachment and Allegiance, supporting the second hypothesis of the study. In contrast, nostalgia did not contribute across stages, while product delivery was only relevant at the Attraction stage and did not significantly predict Attachment or Allegiance.

5. Discussion

The present study aimed to examine whether there are different patterns of brand associations across the stages of the Psychological Continuum Model. The findings demonstrated that activity associations significantly discriminated against the PCM stages and the pattern of associations shift as psychological commitment deepens, supporting the first hypothesis of the study. These results align with theoretical propositions that individuals’ cognitive and affective structures evolve across psychological involvement levels (Karagiorgos et al., 2025) and extend prior research (Alexandris et al., 2017; Gladden & Funk, 2001, 2002; Kaynak et al., 2008) by demonstrating that, along with personal factors, brand meaning itself is also stratified across these stages. They also align with the definitions of customer experience in the tourism context as a multidimensional construct, including both the emotional and intellectual facets, resulting from external (e.g., social, physical, and product-related), internal (e.g., motives), and situational (e.g., co-participants) stimuli (Veloso & Gomez-Suarez, 2023). Product delivery-related associations significantly predicted PCM membership in the Attraction stage only. This pattern suggests that newcomers rely primarily on functional evaluations when forming their initial impressions of the activity. Novice participants assess whether the slopes appear appealing, whether infrastructure is reliable, and whether the overall environment aligns with their expectations of a worthwhile leisure experience. These associations operate as entry-level cues, grounding low-experience individuals in concrete, utilitarian assessments that help them reduce uncertainty before deeper involvement develops. This finding aligns with previous research demonstrating the central role of product attributes in consumers’ early cognitive evaluations (Karagiorgos et al., 2023, 2025).

On the other hand, tradition was shown as a consistent predictor across all PCM stages, which suggests that it functions as a core brand association, as described by K. Keller (1993), providing a stable indicator that influences the activity brand regardless of participants’ involvement level. Beyond its role as a unifying attribute, tradition appears to operate as a cultural resource that legitimizes the activity and reinforces its symbolic continuity, aligning with cultural branding perspectives. To capture this dual function, we propose a two-layer model of activity brand equity. The first layer consists of enduring associations—such as tradition—that provide a stable identity anchor across all PCM stages. The second layer comprises dynamic experiential associations (e.g., excitement, social interaction), which fluctuate systematically across the PCM stages. From a descriptive nature, this dimension expresses the symbolic elements of winter sports, where culture and lifestyle shape the activity’s identity. This is in line with previous research in which it was reported that the key role of tradition related to associations in consumers’ decision-making processes (D. Funk et al., 2023; K. L. Keller, 2020; Kunkel et al., 2013; Wear et al., 2018). Moreover, tradition’s stability across stages indicates its important role. Its presence in the Allegiance stage indicates that long-term participants internalize tradition-related associations as part of their personal identity and lifestyle. Consistent with research on outdoor leisure and adventure tourism (Huang et al., 2015; Karagiorgos et al., 2023), functional attributes matter most when involvement is low, whereas symbolic attributes remain influential throughout the entire psychological spectrum (Alexandris et al., 2017; D. Funk et al., 2023; Kunkel et al., 2014). This provides empirical support for a developmental view of brand meaning, where engagement shifts participants from attribute-based evaluation toward a symbolic representation.

Benefit-based associations reflect participants’ social and psychological benefits as a result of their participation (D. C. Funk & James, 2001). Specifically, escape and peer acceptance differentiated across the stages of PCM. Escape was significant for both Attraction and Attachment stages but not for the Allegiance stage. This finding suggests that early-stage and mid-stage participants rely on experiential benefits, such as freedom from daily stress and relaxation. For individuals in the higher stages of PCM, skiing becomes less about temporary escape and more about expressing a lifestyle identity. This pattern might reflect a deeper internalization of the activity and an extension of one’s self-concept (Alexandris et al., 2017; K. L. Keller, 2023; Lock et al., 2012), supporting the second hypothesis of the study. In the higher stages, skiing becomes less about escaping and more about expressing a lifestyle identity (Alexandris et al., 2017; K. L. Keller, 2023; Lock et al., 2012). Peer acceptance, conversely, was significant across all stages. This underscores the inherently social nature of winter sports and shows peers’ recognition as an enduring symbolic benefit. Previous studies have consistently shown that social-related motives are among the most important ones on individuals’ decisions to start active recreation (Havitz & Mannell, 2005). Even among highly committed skiers, social approval reinforces emotional connection, suggesting that winter sports maintain strong community norms and expectations that influence perceptions regardless of the involvement level. Nostalgia was not a significant predictor across stages, which contrasts with studies in sports fans contexts (Gladden & Funk, 2001; Kaynak et al., 2008; Kunkel et al., 2013, 2014). This disparity suggests that the impact of nostalgia may be dependent on context. A clear theoretical distinction can be drawn between embodied participation activities and spectator sports consumption, as they rely on fundamentally different experiential and cognitive processes. Embodied participation activities—such as skiing—are characterized by direct sensorimotor engagement, where individuals are immersed in immediate perceptual stimuli (e.g., speed, terrain, and bodily coordination) and experience heightened physiological arousal. These activities align with the escapist and esthetic realms of the experience economy (Pine & Gilmore, 1998), in which multisensory immersion anchors attention firmly in the present moment. In contrast, spectator sports consumption is primarily symbolic, relying on long-term emotional bonds with teams or athletes. Because nostalgic associations rely on a reflective, memory-based processing that unfolds over time, they are less likely to surface when individuals are deeply absorbed in high-intensity, present-focused, embodied experiences.

Attitudinal associations reflect the depth of cognitive and emotional internalization of the activity (K. Keller, 2003; K. L. Keller, 2020). Knowledge-influenced Attraction and Attachment both weakened at the Allegiance stage. In other words, for participants at higher levels of commitment, additional knowledge no longer plays a major role. On the other hand, importance and affective reactions became significant only at the higher stages of Attachment and Allegiance. Subsequently, as involvement is increased, the activity becomes associated with personal identity, values, and emotional experiences. These associations indicate that, for more committed participants, the activity is no longer evaluated solely through functional performance but becomes integrated into their self-concept and emotional life. Incorporating this model within existing sport brand equity frameworks (e.g., K. Keller, 1993; Alexandris et al., 2017) and destination brand equity research (e.g., Konecnik & Gartner, 2007) can show how participatory, co-created activity brands differ from spectator-oriented or place-based brands. In this way, this research is consistent with the leisure and sport literature (Gladden & Funk, 2002; D. Funk et al., 2023; D. C. Funk & James, 2001). Specifically, importance reflects subjective meaningfulness, while affective reactions represent emotional resonance. Their emergence at the higher stages of the model demonstrated that attitudinal associations mark the transition from enjoyment to commitment (D. Funk et al., 2023; Kunkel et al., 2014). This result extends the PCM literature by demonstrating that cognitive and affective brand constructs follow distinct patterns across the model’s stages. The unexpected lack of influence from nostalgia warrants particular attention. While nostalgia has been shown to influence sports consumption in some contexts (Cho et al., 2019), its non-significance here suggests that nostalgic cues may be less relevant to differentiate individuals in the different stages. These results, however, require further research.

5.1. Managerial Implications

These results have practical implications for marketers, destination managers, and policy makers responsible for designing customer experience strategies in active sport tourism. First, attracting novice participants requires emphasizing functional performance elements—such as slope quality, safety, accessibility, and infrastructure reliability. Marketing communications should reduce uncertainty by clearly showcasing product delivery, using transparent safety information, introductory packages, and visible service guarantees. These cues help visitors first evaluate the destination and lower perceived risk, which is essential for converting awareness into initial participation. Second, for more experienced participants, brand strategies should highlight the cultural and lifestyle dimensions of winter sports. Storytelling about history, local traditions, and community heritage can foster belonging and strengthen identity-based engagement. Ski resorts can leverage narratives of legacy, local culture, and participant involvement to enrich symbolic meaning and differentiate themselves in a competitive tourism market. This aligns with the broader shift toward experience-driven tourism, were cultural authenticity and emotional resonance shape visitor satisfaction and loyalty. Third, escape-oriented messaging is particularly effective for early-stage participants. Positioning skiing as a refreshing break from routine—supported by well-oriented services, scenic imagery, and restorative experiences—can enhance early involvement. For participants in the Attachment stage, combining escape with social programming (e.g., group lessons, après-ski events, and themed weekends) can reinforce mid-level loyalty by blending experiential and social benefits. Fourth, for loyal skiers, campaigns should emphasize community prestige, exclusivity, and group identity. Niche programs, ambassador roles, loyalty clubs, and community-driven events can capitalize on the enduring influence of peer acceptance. To cultivate higher involvement stages, managers should design emotionally rich experiences—such as personalized services, immersive storytelling on social media, or thematic events—that frame skiing as a lifestyle rather than a single activity. Highlighting the meaningfulness and emotional resonance of the activity can further strengthen attitudinal ties and encourage long-term commitment. Taken together, these findings highlight that brand associations operate as stage-specific psychological markers that can guide strategic decisions in tourism and hospitality. For destinations and resorts, functional associations matter most for newcomers, underscoring the need for clear communication about infrastructure, safety, and service reliability to attract first-time participants. As involvement deepens, experiential and symbolic associations—such as tradition, social belonging, and emotional resonance—become more influential, suggesting that experience design, community-building initiatives, and cultural storytelling should be prioritized for more committed visitors. The emergence of attitudinal associations at higher stages further indicates that advanced skiers respond to identity-based messaging and emotionally rich service environments. These insights can inform destination branding, segmentation strategies, resort programming, and policy initiatives aimed at fostering sustainable active sport tourism. By demonstrating that brand meaning evolves systematically across PCM stages, this study provides a framework for aligning tourism offerings with the psychological needs of different visitor groups, ultimately enhancing satisfaction, loyalty, and long-term participation.

5.2. Limitations and Future Research

First, the study employed a cross-sectional design, which limits the ability to draw causal inferences about transitions between PCM stages. A longitudinal design would be necessary to examine the dynamic causal relationships among the stages and to capture how individuals progress through them over time. The relatively low response rate along with the use of a non-probability sampling method is also a limitation of the study. Findings therefore cannot be assumed to be representative of the broader Greek ski participant population, and any generalizations should be made with caution. In this way, the cultural aspects of the Greek sample should also be noted. Using samples of different countries and skiers of different nationalities could further show if our findings are consistent across different cultures. Also, sensitivity analyses excluding the smallest group (Attraction) yielded consistent patterns, suggesting core findings are robust to sample skewness. Some of the dimensions of brand associations such as tradition and nostalgia might be culturally dependent. The study also acknowledged the skewed distribution of respondents—particularly the high concentration in the Allegiance stage and the comparatively few participants in the Attraction stage. It also recognized the influence of the sampling approach, noting that on-site convenience sampling and QR code recruitment are likely to attract more frequent skiers. However, no robustness tests were conducted to further assess the stability of these patterns. The sensitivity analyses were performed by altering the reference category and assessing potential multicollinearity among predictors. The direction and significance of the key predictors, as well as the VIF values, remained stable across all model specifications, indicating the robustness of the multinomial regression results. A final note should be made about the skewed distribution of PCM stages in our sample, with a disproportionately large share of participants classified in the Allegiance stage and comparatively few in the Attraction stage. This pattern likely reflects the on-site convenience sampling strategy, as QR code recruitment at ski resorts tends to attract more frequent and committed skiers, while individuals with low involvement may be less willing to participate. Such an imbalance may influence the stability of the regression estimates: larger groups (e.g., Allegiance) typically yield smaller standard errors, whereas small groups (e.g., Attraction) may produce less stable coefficient estimates and wider confidence intervals. Future research should employ stratified sampling or complement on-site recruitment with online channels to ensure more representative coverage of early-stage participants.

6. Conclusions

The study demonstrates that brand association patterns vary systematically across the stages of PCM. Functional cues are more salient for newcomers, whereas symbolic and emotional associations gain prominence in the higher stages of involvement. Tradition emerges as a stable association that persists across all stages. Collectively, these patterns indicate that brand meaning in winter sports is stratified, shaped by the interplay of functional evaluations, social benefits, and emotional internalization. The findings extend tourism and sport brand literature by illustrating how sport activity brand characteristics evolve within participatory contexts and underscore the need for further research on demographic, cultural, and contextual factors that may influence these patterns.