The European football industry boasts a staggering market valuation of €45 billion, as reported by the Deloitte Sports Business Group in 2024. This impressive figure highlights the essential need for clubs, ranging from grassroots to elite levels, to strategically optimize their revenue streams. With matchday revenues accounting for a significant 23-26% of total club income, gaining insights into consumer behavior surrounding ticket purchasing decisions is not only an important academic inquiry but also a practical necessity for sports management professionals. Understanding these dynamics can enable clubs to tailor their marketing strategies, enhance fan engagement, and ultimately drive financial success in an increasingly competitive landscape.

Football clubs generate revenue through three primary channels (Georgievski et al., 2019; Georgievski et al., 2024): Matchday revenue from ticket sales and stadium-related activities Television and broadcasting rights Commercial income, including sponsorship agreements

According to Deloitte's report (2024), matchday revenues constituted 23-26% of total revenues, broadcasting accounted for 43-44%, and commercial revenues represented 31-33%. The revenue structure varies between top-tier clubs (with greater emphasis on commercial income at 48%) and lower-ranked clubs (with greater reliance on broadcast revenue at 47%). The dramatic decline in matchday revenues during the COVID-19 pandemic—dropping to merely 1% of total revenue compared to 15% in the 2024/2025 season—underscores the critical importance of spectator attendance. Premier League clubs alone generate 932 million euros from matchday revenue.

Given the significance of ticket sales to overall revenue, football clubs continuously seek strategies to maximize this income stream (Shapiro & Drayer, 2014). From the consumer perspective, the ticket purchasing landscape has grown increasingly complex. Modern sports fans navigate numerous digital platforms to acquire tickets, some controlled by sports organizations themselves and others operated independently. While online shopping has transformed consumer behavior across industries, the accessibility of secondary ticket markets is particularly significant for live sporting events due to their unique characteristics.

Over the past decade, secondary ticket markets have become the primary channel for purchasing tickets to both concerts and sporting events (Won, 2021). The ticket-buying decision process involves multiple considerations that consumers evaluate simultaneously. One crucial aspect is partitioned pricing—the division of a product's price into a base component and additional smaller parts (Morwitz et al., 1998). This practice has proliferated with the expansion of online retail (Greenleaf et al., 2016). While rational economic theory suggests consumers should focus solely on total price rather than its constituent parts, empirical evidence indicates that consumers respond distinctively to partitioned pricing by not fully accounting for additional fees (Voester et al., 2017).

It is with this perspective this study seeks to understand the role of consumer behaviour in purchase of football tickets on customer satisfaction and purchase intentions.

Stakeholder Identification

This research provides valuable insights for various stakeholders within the sports and digital commerce ecosystem. This research offers crucial insights that are beneficial to various stakeholders in the sports and digital commerce ecosystem. Football Club Management can utilize these findings to enhance pricing strategies and boost matchday revenues, which account for 23-26% of the club's total income. Digital platform operators involved in ticket sales need to understand how different pricing formats influence consumer behavior to enhance their services and user experience. Sports Marketing Professionals can leverage insights on consumer behavior to design targeted promotional campaigns that resonate with fans’ emotional connections to their teams. Policymakers will find this information helpful in developing regulations that ensure consumer protection in online ticket markets, with a focus on pricing transparency and clear fee disclosures. Academic Researchers in sports economics and consumer psychology will benefit from expanded knowledge on how emotional attachment and team identification shape economic decision-making in sports.

Research Gap Statement

While existing research has explored partitioned pricing in e-commerce, few studies have focused on its effects in the emotionally charged context of European football. The unique characteristics of sports consumption—such as strong emotional ties and varied pricing models—require targeted investigation.

This study addresses this gap by examining how partitioned pricing versus all-inclusive pricing impacts Eredivisie football fans', price fairness, customer frustration, customer satisfaction, and purchase intentions. It offers critical insights into an industry where fan emotions may override traditional economic reasoning.

This section provides a comprehensive overview of the theoretical frameworks that underpin consumer behavior in the context of purchasing decisions. It explores key factors influencing purchase intentions and customer satisfaction, drawing on findings from prior studies. Additionally, this review establishes the theoretical foundations for the conceptual model that guides the present research.

Pricing Strategies

The way prices are presented strategically influences consumer decision-making processes. This study focuses on two primary pricing strategies commonly used in online sports ticket markets: partitioned pricing (PP) and all-inclusive pricing (AIP). Partitioned pricing separates a product’s total cost into multiple components—usually a base price plus additional fees—whereas all-inclusive pricing consolidates the cost into a single, comprehensive price (Morwitz et al., 1998). Although these approaches are economically equivalent in theory, behavioral economics research reveals that consumers respond differently to each, affecting perceptions and purchasing behavior.

Partition Pricing in Sports

Despite extensive research on partitioned pricing (PP) within the broader marketing literature, its application and effects in the sports context remain insufficiently explored. Notably, some studies have discussed PP in relation to perceived price fairness but have not directly tested its impact in experimental settings (Shapiro, Dwyer, & Drayer, 2016). This gap is particularly striking given the widespread use of partitioned pricing in sport ticket markets, especially as digital ticketing continues to dominate. Advances in network infrastructures and end-user technologies have entrenched digital ticket sales as the industry norm, with PP firmly embedded in both primary and secondary ticket markets (Shapiro et al., 2016; Won & Shapiro, 2019a, 2019b). Ticketing platforms, acting primarily as intermediaries, do not add intrinsic value to the tickets themselves (Täuscher & Laudien, 2018) and therefore rely on service or processing fees to generate revenue.

The limited scholarly attention to PP in sport ticketing is further concerning considering its legal and consumer protection implications. The adoption of partitioned pricing has led to multiple class-action lawsuits (e.g., Lee v. Ticketmaster L.L.C., Live Nation Entertainment, Inc., 2018; Schlesinger v. Ticketmaster, 2014) and governmental investigations highlighting risks of consumer exploitation and market manipulation, with fees reported as high as 40% of ticket prices (Clements, 2018).

Early research within sport management has utilized attribution theory (Weiner, 1986; Voester et al., 2017) to examine how sport consumers perceive the sources and characteristics of price components and how these perceptions influence important managerial outcomes. For instance, additional “green” fees supporting environmental initiatives at venues were viewed positively, leading to increased willingness to pay among consumers (Drayer & Greenhalgh, 2015; Drayer, Kunkel, & Greenhalgh, 2016). Conversely, larger fees tend to evoke negative perceptions regardless of their framing (Marquez, 2020). Moreover, consumer attributions of fees—whether directed toward the ticketing platform or the sports franchise—play a critical role in shaping reactions to PP, with fees attributed to teams being perceived more negatively (Marquez, 2020). Recent research also begins to address contextual moderators such as cultural variations, fan intensity, and ticket value (Won & Shapiro, 2019a, 2019b; Marquez, 2020).

Collectively, this emerging body of work suggests that while partitioned pricing is a common practice in sport ticketing, it carries considerable risks, particularly when fees are seen as excessive or when consumers associate these charges directly with their favorite teams. These insights underscore the need for further research on PP’s impact within emotionally charged sports markets such as the Eredivisie football league.

Conceptual Model

This study develops specific propositions that link theoretical predictions to testable hypotheses, based on an integrated theoretical framework. Each proposition incorporates insights from multiple theories to formulate comprehensive predictions about consumer responses to partitioned versus all-inclusive pricing in sports contexts (Greenleaf et al., 2016; Voester et al., 2017).

Role of Attribution Theory in Price fairness perceptions

Attribution theory explains how individuals interpret and assign causes to events or behaviors—particularly whether they attribute outcomes to internal (company-driven) or external (market-driven) factors.  This framework considers how consumers attribute causes to experienced outcomes (Weiner, 1985). When encountering PP, consumers' judgments depend on the balance between the informational effect (price as quality indicator) and sacrifice effect (price as cost) (Völckner et al., 2012). Additionally, perceptions of price fairness significantly influence these assessments (Sheng et al., 2007; Xia & Monroe, 2004). Attribution theory plays an integral role in how football fans view the pricing of the football tickets. If consumers attribute the additional charges of partition pricing to additional charges like service fees, or other uncontrollable factors of stadium maintenance cost or third party processing fees, they may perceive the pricing as fair. On the other hand, if consumers attribute pricing to internal factors like profit motives, they may consider pricing as unfair.

When evaluating price fairness, consumers compare prices against reference benchmarks (Xia et al., 2004), with prices below these benchmarks perceived as fair and those above as unfair (Maxwell, 2002). In online sports ticket markets, pricing structures significantly influence fairness perceptions (Shapiro et al., 2016).

Multiple factors affect how consumers evaluate PP fairness, including: Relative and absolute size of surcharges: Higher fees generally reduce perceived fairness (Carlson & Weathers, 2008; Sheng et al., 2007; Xia & Monroe, 2004). Seller reputation further impacts the perception of price fairness among buyers. Fees appear more acceptable when viewed as unavoidable rather than profit-enhancing (Xia & Monroe, 2004).On the contrary, on the other hand, price transparency may further enhance fairness perceptions (Bambauer & Gierl, 2008; Homburg et al., 2014).

Despite limited research specific to Eredivisie and other sports leagues, studies suggest that PP generally reduces perceived price fairness in sports ticket contexts (Hayduk et al., 2021), aligning with findings from other service industries (Feurer et al., 2015; Mukherjee, 2022). This negative effect may be particularly pronounced for hedonic purchases like football tickets (Baghi et al., 2010).  Given the negative effect of partition pricing in various hedonic categories in the previous literature, this study formulates its first hypothesis is: 

• H1: The use of Partition pricing leads to lower price fairness as compared to participants facing All inclusive pricing.

Role of Prospect Theory in Understanding Customer Satisfaction and Frustration

According to prospect theory devised by Kahneman and Tversky (1979), individuals evaluate gains and losses relative to specific reference points, with losses inducing stronger negative feelings than equivalent gains provide positive feelings. In the partitioned pricing scenario, prospect theory helps explain why customers may feel frustrated or dissatisfied, even when the total price remains reasonable. Since PP creates multiple loss experiences through separate charges, it can generate more negative perceptions than AIP's single loss experience (Schindler et al., 2005). This aligns with mental accounting theory, wherein consumers remember price components in distinct mental accounts, potentially creating a segregated loss perception that reduces overall utility (Kim & Kachersky, 2006).

Customer frustration—an intensified form of dissatisfaction arising when expected outcomes remain unmet (Stauss et al., 2005)—represents a critical but understudied response to PP. In online ticket purchasing, frustration may emerge when unexpected surcharges appear during checkout (Won & Shapiro, 2021), potentially triggering negative responses including complaints and avoidance behaviours (Tuzovic et al., 2014).

The overall customer frustration from partition pricing has been further linked to lower customer satisfaction in various studies (Drayer & Shapiro, 2011). Transparency plays a crucial role while presenting fans with partition pricing in context of sports due to strong emotional investment. A lack of transparency can harm consumer perception about price fairness and impact satisfaction in long run (Kim & Trail, 2011). To further extend this work, this study hypothesises a negative impact of partition pricing on customer satisfaction and an increased frustration from the buying process. The next two hypothesis for this study are:

• H2: Partition Pricing is expected to increase customer frustration as compared all inclusive pricing scenario
• H3: Partition Pricing is expected lower customer satisfaction as compared to all inclusive pricing scenario

Role of Dual Process Theory on Purchase Intentions

The Dual-Process theory by Kahneman (2011), in the sports context of partitioned pricing refers to how fans process pricing information using two distinct cognitive systems—System 1 (fast, intuitive) and System 2 (slow, analytical). Integrated Theoretical Framework. System 1 (fast, automatic, intuitive) and System 2 (slow, deliberate, analytical). When sports fans encounter partitioned pricing, they initially process information through System 1 thinking, which is particularly susceptible to anchoring bias. This automatic processing causes consumers to focus disproportionately on the base price (the anchor) while inadequately adjusting for additional fees. However, when consumers switch to System 2 thinking—either through deliberate effort or when surcharges become noticeable—they may more accurately calculate total costs. However, they may also experience the emotional impacts described by Prospect Theory.

With regard to purchase intentions, many studies have noted a declining purchase intention when faced with partition pricing as compared to all inclusive pricing (Drayer & Shapiro, 2009, Kim, Natter, & Spann, 2009). Research indicates that perceived value significantly mediates the relationship between various factors and purchase intention in sports contexts (Drayer et al., 2018; Kwon et al., 2007; Murray & Howat, 2002). Similarly, perceived price fairness influences purchase likelihood, with PP potentially decreasing purchase intentions through reduced fairness perceptions (Feurer et al., 2015; Mukherjee, 2022). The extension on this literature provides the backing for the next hypothesis:

• H4: Partition pricing is expected to lower the purchase intention as compared to all inclusive pricing scenario

Role of Team Identification Theory and Moderating Effects on Partition Pricing

The context of sports consumption adds important complexity to this dual-process model. Unlike typical commercial transactions, sports ticket purchases involve significant emotional investment and components of social identity. Team Identification Theory, rooted in Social Identity Theory (Tajfel & Turner, 1979), suggests that highly identified fans process pricing information through an emotional lens that can override rational economic evaluation. This emotional processing may shift the balance between System 1 and System 2 thinking, with strong team identification potentially maintaining dominance of System 1 even when pricing discrepancies are apparent. Additionally, the hedonic nature of sports consumption (Hirschman & Holbrook, 1982) indicates that fans prioritize emotional satisfaction over functional utility, which can diminish the explanatory power of traditional economic theories.

Despite these concerns, habituation to PP through extensive online exposure may mitigate negative effects (Won & Shapiro, 2021), and sports enthusiasts' reduced price sensitivity (Kwon et al., 2007) may further diminish adverse impacts on purchase intentions. Among other factors, gender can moderate the impact differently among male and female football fans. Dietz, Bean, and Omaits (2021) found that males were more likely than females to consider themselves a fan of sport and engaged significantly more in traditional fan behaviors. James and Ridinger (2002) also found that male fans show stronger motivation to purchase related to sport identification. Given the role of gender on purchase intentions, this study formulated its next hypothesis:

• H5: Purchase intention is expected to be higher among male fans as compared to female fans

Team Identification as Moderating effects

Team Identification Theory, based on Tajfel and Turner's (1979) Social Identity Theory, provides valuable insights into how emotional attachment to sports teams influences economic decision-making. Fans who strongly identify with their teams view them as an extension of their identity, resulting in a psychological investment that goes beyond traditional cost-benefit analysis. This identification means that pricing strategies may have different effects depending on the strength of the fan-team relationship.

Sports elicit powerful emotions in fans through team identification (Marquez et al., 2022), with strongly identified fans demonstrating greater willingness to pay (Drayer & Shapiro, 2011) and reduced price sensitivity (Kwon et al., 2007). This effect potentially amplifies PP's impact, as Morwitz et al. (1998) demonstrated that PP positively influences demand for preferred brands in competitive scenarios.

Furthermore, the distinction between hedonic and utilitarian consumption (Hirschman & Holbrook, 1982) provides additional context for understanding sports ticket purchasing behavior. Sports consumption primarily reflects hedonic value, where fans seek emotional experiences, social connections, and the expression of identity rather than practical utility. This hedonic focus suggests that traditional price sensitivity may be lower, as fans prioritize the emotional benefits derived from attending events over economic efficiency. As a result, the effects of partitioned versus all-inclusive pricing may be influenced by the experiential nature of sports consumption.

Lastly, Sports Fan Behavior Theory (Funk & James, 2001) introduces another layer of complexity by acknowledging that fan behavior exists on a continuum ranging from casual interest to deep psychological connection. This continuum indicates that the effectiveness of pricing strategies can vary significantly among different fan segments, with highly committed fans potentially reacting differently to partitioned pricing compared to casual consumers. By integrating these sport-specific theories with traditional economic models, we gain a more nuanced understanding of how pricing strategies affect consumer behavior in the sports context.

Given the complex relationship and role of various factors on purchase intention this study aims to measure the combined effects of age, gender, team identification and partition pricing scenarios versus all inclusive pricing on purchase intentions. The combined effects are hypothesised to be tested by the following multiple regression model:

- Equation 1

Survey Set-up

Given that approximately 80,000 fans attend all the Eredivisie football matches during a season, a sample size of 200 was estimated to be adequate given 90% confidence interval, six  percent margin of error. The study aimed to target 200 survey responses via self selection method of sampling and received 150 total responses. After the data cleaning, 139 responses were processed for the final analysis. The study is based on the concepts of descriptive research as it allows to identify the characteristics and viewpoints of a representative sample drawn from a population. The foundation of the study lies on a cross sectional survey, set up Qualtrics. The study utilised non-probability method of convenience and self selection method of sampling. The data was collected via various social media fan pages, and via online platform survey like SurveyCircle and SurveySwap. The technique of non probability sampling was chosen to maximise the number of responses, given limited time and resources.

Questionnaire Design

The survey focussed on gathering basic demographic information like gender, and age. The survey asked participants about their favourite football club (later called team identification). After the collection of basic data, the survey started a unique simulation for each Eredivisie team where they played Ajax or Feyenoord. These two teams were selected based on their success in the last season and due to their popularity. Therefore, regardless of fandom level, every fan identifies these matches to be important. In next step of the simulation, respondents were provided a stadium overview with an option to choose three categories of seats with low, average and high quality, with corresponding prices. The seat categories and pricing were established based on current prices on the official websites, and internet webpages.

During the simulations the respondents were randomly assigned to two scenarios of Partition Pricing (PP) and All Inclusive Pricing (AIP). Although both pricing structures had same total price in euros, the PP scenario added a 10% service fees during checkout.  Studies by Voester, Ivens, and Leischnig (2017) and Greenleaf, Johnson, Morwitz, and Shalev (2016) suggests base price and surcharge fee to be 90% and 10% of total costs, respectively. The choice of PP vs AIP was captured to understand its impact on customer behaviour and purchase intentions. 

The next section of the survey asked participants their agreement level with several statements on a 7 point Likert scale ranging from 1 (Strongly disagree) to 7 (Strongly Agree). The statements captured the constructs of Price fairness, Customer Frustration, Customer Satisfaction and Purchase Intentions. The construct of Price Fairness was adapted from Xia, Monroe, & Cox (2004). Customer Frustration was measured through 5 statements retrieved from studies by Guchait & Namasivayam (2012) and Tuzovic, Simpson, Kuppelwieser, & Finsterwalder (2014), whereas the evaluation of Customer Satisfaction was evaluated based four statements from SERVQUAL scale used by Parasuraman, Zeithaml, & Berry (1988). The construct of Purchase Intention was measured via four statements based on the research from other sports related studies (Suh, Ahn, Lee & Pedersen, 2015).

Data Modification & Methodology

The collected data was modified to create a categorical variable for participants who faced Partition Pricing (PP) as 1, and 0 for those who faced AIP. The Likert scale items of Price fairness, Customer Frustration, Customer Satisfaction and Purchase Intentions  were converted into compound means for further calculations. The reliability of the questionnaire was tested by Cronbach alpha. The results of reliability are considered significant if Cronbach alpha attains a value of .70 or more. 

Descriptive Statistics

The descriptives statistics of the study are presented in Table 1 and Table 2. The respondents for the survey were mostly males (63%), followed by females (37%). The simulation of football ticket purchase showed 50% participants a scenario of partition pricing, and remaining 50% the all inclusive pricing. The respondents who responded to have a favourite team were identified via team identification, amongst the total respondents 76% had a favourite team. The descriptive statistics in table 2 presents mean and standard deviation of the key variables of this analysis. The average response on Likert scale agreement reflects a higher agreement level for Purchase intentions, customer satisfaction, and price fairness as compared to customer frustration.

• Insert Table 1on Descriptive Statistics for Categorical Variables about here
• Insert Table 2 on Descriptive Statistics for Likert Scale Responses about here

Diagnostic Tests 

The diagnostics tests on reliability which is indicated by Cronbach alpha values are presented in Table 3. The value of Cronbach alpha above .70 indicates item reliability. The variables in this analysis meets the cut-off criteria for all variables of analysis. The internal consistency is deemed good for Customer frustration, and Customer Satisfaction with values of The same indicator can be considered excellent for Price fairness and Purchase Intentions given the .

Insert Table 3 on Summary of Reliability Analysis for the Questionnaire insert here

The results from the independent samples t-tests for Hypotheses 1–5 are presented in Tables 4–8. Hypothesis 1 focused on assessing differences in perceived price fairness between partitioned pricing and all-inclusive pricing. While the mean fairness rating was slightly lower for partitioned pricing, the results (Table 4) indicated no statistically significant difference in perceived price fairness between the two pricing strategies (t(137) = -0.769, p = 0.443). Therefore, the role of attribution theory in lowering price fairness expectations could not be supported by this analysis.

Insert Table 4 Comparison of Price Fairness Between Partition and All-Inclusive Pricing Using a t-Test on about here

The next hypothesis speculated that partitioned pricing would increase customer frustration. The results presented in Table 5 confirm this expectation. There is a statistically significant difference in customer frustration between partitioned pricing and all-inclusive pricing (t(137) = 2.184, p = 0.031). Customers reported higher frustration under partitioned pricing, supporting the hypothesis that partitioned pricing elicits a negative emotional response.

The analysis further examined the impact of both pricing types on overall customer satisfaction when purchasing football tickets (Table 6). Hypothesis 3 predicted lower customer satisfaction in the partitioned pricing scenario. While the results in Table 6 indicate a negative impact of partitioned pricing on customer satisfaction, the overall effects were not statistically significant (t(137) = -1.163, p = 0.247). Thus, the role of prospect theory is supported for Hypothesis 2 but not for Hypothesis 3 (Stauss et al., 2005; Tuzovic et al., 2014).

Insert Table 5 on Comparison of Customer Frustration Between Partition and All-Inclusive Pricing Using a t-Test about here

Insert Table 6 on Comparison of Customer Satisfaction Between Partition and All-Inclusive Pricing Using a t-Test about here

Overall purchase intention was hypothesized to be lower under partitioned pricing. The results presented in Table 7 confirm the direction of the relationship; however, the findings were not statistically significant, leading to a rejection of the hypothesis. Specifically, there was no significant difference in purchase intention between partitioned pricing and all-inclusive pricing (t(137) = -0.337, p = 0.737). It should be noted that the role of Dual Process Theory could not be confirmed through this analysis.

The final hypothesis aimed to examine the role of gender in purchase intention, predicting that males would exhibit higher purchase intentions than females, based on Team Identification Theory. The results presented in Table 8 indicate no statistically significant difference in purchase intention between male and female respondents (t(137) = 1.185, p = 0.238). Although males reported slightly higher purchase intentions, the difference was not significant, and thus the findings do not support Team Identification Theory. A summary of the findings for all hypotheses is presented in Table 9. The overall insignificant results may be partly attributed to the relatively low service fees applied in the simulated purchase of sports tickets. In this analysis, a 10% service fee was used under the partitioned pricing condition. It is possible that higher service fees could elicit stronger negative reactions, potentially leading to more pronounced differences in perceived fairness, frustration, satisfaction, and purchase intention. Future research may yield different results by testing scenarios with higher service fee percentages.

Insert Table 7 on Comparison of Purchase Intention Between Partition and All-Inclusive Pricing Using a t-Test about here

Insert Table 8 on Comparison of Purchase Intention by Gender Using a t-Test about here

Insert Table 9 on Summary of Hypotheses Tested about here

The regression results findings from equation 1 presented in table 10 focusses on various moderation effects of partition pricing vs all inclusive pricing, team identification on overall purchase intention of football tickets. The focus of the analysis is to highlight the main effects, of team identification and partition pricing. The overall results indicate a positive and significant impact of team identification on purchase intention (p = .005). The effects of partition pricing and gender were found to be insignificant. Age could be considered significant at 10 percent level of significance. The overall findings highlight lower purchase intentions for older age groups.

The model explains 11% variation in purchase intentions depicting modest explanatory power. The model is statistically significant with overall ( p = .024), indicating the role of at least one predictor significantly explaining variation in purchase intentions. The variance inflation factor (VIF) values for the predictors are near one, indicating no multicollinearity. The regression results confirms the team identification theory, whereby fans who strongly identify with the team are significantly more likely to buy tickets, regardless of how the price is presented. The hedonic consumption patterns are further supported by this result, whereby fans prioritize the emotional benefits derived from attending events over economic efficiency.

Insert Table 10 on Regression Results with Purchase Intention as the Dependent Variable about here

This study explored the influence of partitioned pricing (PP) versus all-inclusive pricing (AIP) on consumer perceptions and behaviors within the context of Eredivisie football ticket purchases. Grounded in established theoretical frameworks—including Attribution Theory, Prospect Theory, Dual Process Theory, and Team Identification Theory—this research sought to understand how pricing strategies affect price fairness perceptions, customer frustration, satisfaction, and purchase intentions among sports fans.

The survey-based methodology employed a cross-sectional design, utilizing realistic ticket-purchasing simulations to test the impact of PP and AIP on fans’ psychological and behavioral responses. Constructs were measured using validated multi-item scales, and hypotheses were tested through independent samples t-tests and multiple regression analyses.

The findings provide nuanced insights: partitioned pricing significantly increased customer frustration, confirming the emotional costs associated with multiple fees as predicted by Prospect Theory. However, contrary to expectations, partitioned pricing did not significantly affect perceived price fairness, customer satisfaction, or purchase intentions. These mixed results suggest that the relatively low surcharge (10%) employed in this study may have tempered negative consumer reactions.

Importantly, team identification emerged as a robust predictor of purchase intentions, reinforcing the critical role of emotional and social identity factors in sports consumption. Fans with strong attachments to their teams showed higher willingness to purchase tickets regardless of pricing presentation, underscoring the dominance of hedonic motivations in this context over purely economic considerations.

While the study advances understanding of pricing effects in sports markets, limitations such as sample size, use of convenience sampling, and the modest surcharge level highlight opportunities for future research. Subsequent studies might explore higher surcharge levels, broader fan demographics, and other sports contexts to deepen insights into how pricing strategies interact with emotional and cognitive factors to shape consumer decisions.

Overall, this research contributes valuable empirical evidence to the pricing literature, emphasizing the complex interplay between pricing structures, psychological theories, and fan identity in shaping sports ticket purchase behavior.

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