Introduction
Necessity of research
Globalization, now a worldwide phenomenon, has not only triggered transnational companies to more aggressively carry out their international market expansion strategies but also became a trend in the realm of professional sports. Nicknamed ‘universal language’, sport is one of few industries that transcends nation, culture, and race (Annan, 2005). Given this reality, some sports, especially football, have consistently drawn worldwide fan support for many years (Hill & Vincent, 2006). Despite its popularity in many regions, the actual realization of pioneering the uncharted territories has been a pie in the sky mainly due to barriers created by the physical distance between the teams and the potential fans overseas (Ghemawat, 2001). However, global market expansion opportunities came into a graspable distance thanks to the advances of the Internet and the emergence of mobile platforms (Cohen & Kennedy, 2000; McDonald, Mihara, & Hong, 2004; Santomier, 2008). They have true global reach and allow teams to convey information across borders with ease—according to Kleiner Perkins Caufield and Byers (2015), 73% of the world’s population are mobile phone users. These advancements in the technology landscape boosted the rapid expansion of “satellite fans” which is defined as the fans who enthusiastically support foreign-based teams without shared geography (Bader et al., 2017; Behrens & Uhrich, 2019; Cho, Chiu, & Tan, 2020; Kerr & Gladden, 2008).
Along with its popularity worldwide and advancement in media technologies, professional sports teams (especially European football teams), who once used to operate within their market of origin, now are turning their eyes to greater international markets—especially Asia. Football business between European football teams and Asia has developed at a rapid pace with Asian business millionaires investing in European football clubs (e.g., Leicester City's Thai ownership, Chinese tycoons investing in Atletico Madrid). Moreover, European giants such as Manchester United and F.C. Barcelona are trying to capitalize on football popularity in Asia (Cho, 2013; Richelieu & Desbordes, 2009). This market expansion movement is more frequently evident in top-tier European football teams as they seek to expand their markets internationally through their worldwide popularity (Mason, 1999; Richelieu & Desbordes, 2009; Fleischmann & Fleischmann, 2019). European teams’ market expansion efforts were triggered to broaden their revenue sources and to overcome the challenges posed by matured or saturated European markets (Chadwick, 2007). These market expansion efforts can manifest along different forms, such as signing athletes who originate from the target market, holding international tours, participating in friendly tournaments during the off-season, and launching numerous marketing operations (e.g., the establishment of overseas team merchandise shops, website promotions, etc.) (Bodet & Chanavat, 2010; Chadwick, 2007; Desbordes, 2007; Miles & Rines, 2004). European football teams holding their preseason camps in Asia and the U.S. is one frequently evident example. Although teams undertake these various efforts to expand their market internationally, teams signing the target market’s national athletes is one of the most approachable and effective methods as fans tend to follow the teams that feature their national athletes (Chadwick, 2007; Mason, 1999). Athletes are the most influential human brands who fans associate with the most in the realm of professional sports (L’Etang, 2006; Thomson, 2006) and this form of athlete transfer is more frequently evident as more athletes from those new potential markets (e.g., East Asia—South Korea, Japan, China, etc.) are capable of competing in the European football leagues.
Purpose of the Study
Despite these trends, to date, extant studies have yet to empirically examine the role of a team signing the target market’s national team athlete in international market expansion efforts. In other words, little is known about the effect of athlete signing on team-related outcomes. Therefore, the purpose of the current study was to examine the role of signing a sport national icon—a national team athlete who has nationwide popularity—as a tool for market expansion for professional sports teams.
The authors particularly aimed (1) to demonstrate the effect of the athlete signing on fan loyalty toward the team and (2) to investigate which levels of football involvement have a greater impact on fans’ loyalty toward the teams.
Conceptual Development and Hypotheses
Athlete signing on team loyalty
Professional athletes nowadays are deemed as celebrities who represent human brands (Carlson & Donavan, 2013; Thomson, 2006). Given the popularity, fans tend to have strong connections with the athletes they admire. This connection has been termed identification, defined as “an oneness with or belongingness with an entity where the individual defines him or herself in terms of the entity to which he or she is a member” (Mael & Ashforth, 1992, p. 104). Social identity theory serves as a theoretical foundation for understanding fans’ affiliation with athletes. The theory posits that individuals categorize themselves and others into in- and out-groups intending to achieve positive self-esteem and self-enhancement (Abrams & Hogg, 1988; Tajfel & Turner, 1985). In an athlete-fan relationship, fans are motivated to associate with athletes due to the psychological benefits of such associations. Correspondingly, fans tend to form stronger connections with the athletes who are similar to their actual or ideal self as it contributes to his or her social identity and enhances their self-image (Aaker, 1997; Hogg, Terry, & White, 1995; Tajfel & Turner, 1985). This study anticipates that the aforementioned fans’ association with athletes will have a positive impact on team-related outcomes—team loyalty in the current study. The social identity theory supports the link between signing the nation’s athlete and team loyalty.
Brand loyalty is a measure of consumers’ attachment to a brand and, therefore, is the core of a brand’s equity (Kaynak, Salman, & Tatoglu, 2008). In other words, it is consumers’ favorable attitude, and consistent purchase, towards a particular brand (Wilkie, 1994). As such, team loyalty, in the realm of the professional sports industry, is also a very important term. Wakefield and Sloan (1995) defined ‘team loyalty’ as enduring allegiance to a particular team. Therefore, as loyalty is depicted as consistent behavior or repeat patronage, it is a significant financial goal for many sports teams. According to a former study, team loyalty can be classified into cognitive, affective, conative and action loyalty and this phenomenon can affect each level of loyalty in diverse ways (Yuksel, Yuksel, & Bilim, 2010). According to Thomson (2006), athletes who have a highly identified group of fans can be influential endorsers. Thus, as athletes represent an important brand association for their teams (Gladden & Funk, 2002), athletes can act as direct endorsers of their respective teams. Furthermore, based on the concept of sports ethnocentrism (Hu & Bedford, 2012), former studies found that fans develop team and player identification, which ultimately leads to behavioral consumption, when their nation’s athlete is playing in foreign leagues (Chiu & Won, 2020). Therefore, signing an athlete (particularly with a national icon status) will lead to a more favorable team loyalty evaluation. With these backgrounds, it is hypothesized as follows:
H1: Fans’ loyalty toward the team will be more favorable when the team signs their national team athlete
H1a: Fans’ cognitive loyalty will be more favorable
H1b: Fans’ affective loyalty will be more favorable
H1c: Fans’ conative loyalty will be more favorable
H1d: Fans’ action loyalty will be more favorable
Football involvement and team loyalty
Involvement is concerned with the importance and relevance of the product (either tangible or intangible) to the inherent needs and values of the consumer (Mittal, 1995; Zaichkowsky, 1985). As such, depending on their level of involvement, the individual consumer’s extent of the purchase decision and searching depth of product information varies (Laurent & Kapferer, 1985). Due to such characteristics, consumer product involvement is positively correlated with product knowledge, implying that consumers with a higher degree of involvement tend to be more knowledgeable about the product (Liang, 2012). Therefore, product involvement, which refers to a general level of interest in or concern about a product class (Hupfer & Gardner, 1971), is likely to moderate the athlete signing and team loyalty valuation relations. In other words, highly involved football fans are more likely to be affected by a player’s transfer as fans with high levels of involvement in football are knowledgeable about football. Empirical studies also supported the moderating role of involvement (e.g., Ambroise, Ferrandi, & Valette-Florence, 2005; Xue, 2008; Kim, Ok, & Canter, 2010). Hence, the current study hypothesized that the effect of signing national icons on fans’ loyalty toward the respective team will be moderated by the individual’s degree of football involvement.
Methods
To derive the results of this study, quantitative research methods were used. Concretely, the current study conducted an experimental study and utilized the form of providing stimulus material and questionnaires for the data collection. The collected data was verified using the paired t-test and one-way ANOVA. In addition, Cronbach’s alpha values were used to check reliability, peer review on the questionnaire was conducted and the stimulus was written for four players instead of one player to secure validity.
Participants
Sports fans in South Korea were selected to analyze their loyalty toward the European football teams—i.e., the South Korean satellite fans. A total of 152 survey data was collected at a large national university in Seoul. Students were recruited via their enrollment in sport-related courses. The samples were purposefully selected because the stimuli provided in the study were likely to be relevant to the aforementioned students as they have an interest in sports. After data screening, 136 survey data was used for further analysis, excluding 16 unusable responses. The final subjects consisted of 89 males (65.4%) and 47 females (34.6%). The age groups of the subjects were 3 teens (2.2%), 81 in their 20s (59.6%), and 52 in their 30s (38.2%). The derived results are presented in <Table 1> below.
Procedure
An experimental design was used to collect data. The subjects were asked to read stimulus material and conducted a survey. The material was in a fictitious newspaper article format which was made to appeal to the respondents in a more realistic manner. The stimulus article stated that a specific player with Korean nationality (national team player with nationwide popularity) was transferred to a European football team. The stimulus material was written with four different players. This was purposefully made to maximize the validity of the study. Thus, the four types of stimulus materials were created with four different players who are well-known Korean national team players. The subjects were randomly assigned to one of four stimulus materials. Before presenting the stimulus article, participants’ loyalty toward the signing team was measured. Then, after 4 weeks, the participants were exposed to a fictitious newspaper article and then their loyalty toward the signing team was measured again. Team loyalty was measured as a dependent variable to examine the effects of the stimulus.
Measurement
In order to measure the perceived value and image of a player, the questions proposed by Vogel, Evanschitzky, and Ramaseshan (2008) were modified to fit the context of this study. These items measured value equity and brand equity. The perceived value and image of a player consisted of three items each and all were measured by seven-point Likert scale items. The main questions asked to measure both variables are as follows: (1) perceived value of a player: ‘I think the player is a valuable player.’, (2) perceived image of a player: ‘I think the image of the player is attractive.’
The questions used by Harris and Goode (2004) were adjusted to fit the context of the study and were utilized. In this study, four levels of team loyalty were measured (cognitive, affective, conative, action) and each aspect consisted of three items, and all were measured by seven-point Likert scale items. The main questions asked to measure four levels of team loyalty are as follows: (1) cognitive: ‘the team that comes to mind first when trying to watch football is the team’, (2) affective: ‘to feel the joy through the team’, (3) conative: ‘I want to recommend it to others’, (4) action: ‘I watch the game of the club more often than other clubs’. The subjects’ involvement in football was also measured. Involvement was measured as a moderating variable, and through this, the effect of individual subjects’ interest in football was verified. This was used by revising the items suggested in the study of Shank and Beasley (1998) to fit the research context and was measured by four items. The question contained wordings such as 'I usually have an interest in football'. In addition, in order to verify the difference between the stimuli created by four different players, the perceived value and the image of the players were measured.
Data analysis
In order to secure the reliability of the collected data, before proceeding with further analysis, Cronbach’s alpha verification was conducted to confirm whether a value of 0.7 or more was obtained. Next, the paired t-test and One-way ANOVA method were utilized to analyze the collected data. For validity, the questionnaire was reviewed by peers, and the opinions were collected and adjusted to make the phrase of the questions easier to understand. First of all, to verify the difference between the stimuli, a one-way ANOVA was conducted to analyze the perceived value and the image difference among the players as a manipulation check. After that, the difference in team loyalty was examined. The first step was to examine whether there was a difference between before and after providing stimuli by dividing the entire response data into cognitive, affective, conative, and action loyalty. After that, the verification of the difference between pre- and post-stimulus overall team loyalty.
In the second step, the data was divided into three groups according to the subjects’ level of football involvement. The group belonging to the bottom 33% was classified as the lower group, the group lying between 33% and 66% was named the middle group, and the group belonging to the top 33% was the high group. Practically the authors classified low, middle, high involvement groups as follows: 3.5 or less as a lower group (46 responses), between 3.8 and 5.8 as a middle group (48 responses), and 6.0 and above as a high group (42 response). The analysis aimed to examine the difference in team loyalty before and after providing the stimulus. This was analyzed through one-way ANOVA with the mean difference of loyalty between before and after providing the stimulus. The IBM SPSS statistics 24 program was used to carry out all the analyses.
Results
Manipulation check
First, the perceived value and image of the player were measured to verify whether the stimulus actually had an effect. Looking at the derived results, the overall perceived value was 4.6 and the overall perceived image was 4.4. Looking at each player, the perceived values were 5.1, 4.6, 4.3, and 4.2, and the overall perceived image was 4.7, 4.2, 4.0, and 4.5. For one-way ANOVA, as a first step, the variance homogeneity between groups was verified using the Levene statistic, and the results were all <.5 (perceived values: .002, perceived image: .008), indicating that the equal variance was not satisfied. Therefore, a homogeneity robust test of the mean was additionally performed using the Welch and Brown-Forsythe tests. Looking at the results, it was found that there were significant differences among groups in terms of the perceived values. Specifically, the F-value was calculated as 4.1(Value)/1.6 (Image) and the significance probability was calculated as .008(Value)/.204(Image) for the perceived values and image, respectively. In the case of the Welch and Brown-Forsythe test results, the significance probability of the perceived values and image were .001/.008(Value) and .168/.193(Image), respectively.
Based on these results, post-hoc analysis was conducted in terms of the perceived values. Tamhane, Dunnett T3, and Games-Howell, which are used when equal variance is not assumed, were all verified. It was found that there was a significant difference between player 1 and player 3 (.017/.017/.015) / player 4 (.002/.002/.002). The derived results are presented in <Table 2> and <Table 3>. As a result of the analysis, it was found that Player 1 had a difference in perceived value from other players, so in further data analysis, the result excluding Player 1 was additionally presented through the notation in parentheses.
The effect of signing players
Looking at the results of reliability verification through Cronbach’s alpha for the measured value, it was confirmed that all the measured variables were .7 or higher. Through this, it can be assumed that the reliability of the measured data was secured. Specifically, in the case of team loyalty, the results of cognitive, affective, conative, and action loyalty measured before providing the stimulus were identified as .779, .883, .914, and .847, respectively, and the overall result was .937. In the case of the measured values after reading the stimulus, the results of cognitive, affective, conative, and action aspects were .915, .891, .889, and .930, respectively, and the overall result was .951. In the case of football involvement and perceived value and image, reliability was also secured as the values were .943, .872, and .932 respectively. Detailed results are presented in <Table 4>.
Table 4.
Reliability verification result
| Variable | Stage | Aspect | α Value | α Total |
|---|---|---|---|---|
|
Team Loyalty |
Before | Cognitive | .779* | .937* |
| Affective | .883* | |||
| Conative | .914* | |||
| Action | .847* | |||
| After | Cognitive | .915* | .951* | |
| Affective | .891* | |||
| Conative | .889* | |||
| Action | .930* | |||
| Involvement | .943* | |||
| Value | .872* | |||
| Image | .932* |
The change in team loyalty before and after reading the stimulus article was measured using the paired t-test. First, t-value and p-value were derived as -12.6(-9.9) and <0.01(<0.01), respectively, which shows that there was a significant difference. It was confirmed that the difference between the averages was -1.8(-1.7), and the team loyalty was increased after reading the stimulus. Looking at each level of loyalty, in the case of cognitive and affective loyalty, the t-value and the p-value with the mean difference was found to be -16.1/-11.3(-12.5/-8.9), <.001/<.001 (<.001/<.001), -2.5/-2.0(-2.3/-1.8), respectively. For conative and action loyalty, t-value and p-value with the mean differences were found to be -10.1/-7.3 (-7.6/-6.8), <.001/<.001(<.001/<.001) and -1.7/-1.2 (-1.5/-1.2), respectively. Through this, it was found that there was a difference in every level of team loyalty before and after exposure to the stimulus. In the case of the data analysis excluding the player 1 related responses, a difference was also significant in every loyalty level. These results provided support for H1 and the sub hypotheses. Detailed results are presented in <Table 5>.
Table 5.
Pre/Post Team Loyalty Difference Verification Results
| Variable | Aspect |
Mean Difference |
SD | t | p |
|---|---|---|---|---|---|
|
Team Loyalty |
Cognitive |
-2.5 (-2.3) |
1.8 (1.8) |
-16.1 (-12.5) |
<0.001* (<0.001*) |
| Affective |
-1.9 (-1.8) |
2.0 (2.0) |
-11.2 (-8.9) |
||
| Conative |
-1.7 (-1.5) |
2.0 (1.9) |
-10.1 (-7.6) |
||
| Action |
-1.2 (-1.2) |
1.9 (1.9) |
-7.3 (-5.8) |
||
| Total |
-1.8 (-1.7) |
1.7 (1.7) |
-12.6 (-9.9) |
The moderating effect of football involvement
Before proceeding with the analysis, the team loyalty (before and after providing the stimulus) of the three involvement groups was analyzed through paired t-test. The results showed a difference for total loyalty and every loyalty level between of pre- and post-stimulus regardless of the presence of player 1 related responses. Specific results are presented in <Table 6>. Prior to conducting the one-way ANOVA analysis, a preliminary analysis was undertaken. As a first step, the variance homogeneity between groups was verified using the Levene statistic and the results were all <.5(<.5), indicating that the equal variance was not satisfied. In detail, the probability of significance was calculated as .491(.485), .303(.130), .408(294), .027(237), and .137(.085) in the order of cognitive, affective, conative, action loyalty, and total loyalty respectively. Therefore, a homogeneity robust test of the mean was additionally performed using the Welch and Brown-Forsythe tests.
Table 6.
Pre/Post Team Loyalty Difference Verification Results by Group (Paired T-test)
| Group | Aspect | Mean | SD | t | p |
|---|---|---|---|---|---|
|
1 Football Involvement > 3.5 |
Cognitive |
-2.6 (-2.3) |
1.9 (20.0) |
-8.9 (-6.6) |
<0.001* (<0.001*) |
| Affective |
-2.6 (-2.3) |
2.1 (2.2) |
-8.2 (-5.7) |
||
| Conative |
-2.3 (-2.0) |
2.1 (2.0) |
-7.7 (-5.1) |
||
| Action |
-1.6 (-1.5) |
2.2 (2.2) |
4.9 (-3.9) |
||
| Total |
-2.3 (-2.0) |
1.9 1.9) |
-8.2 (-6.0) |
||
|
2 Football Involvement 3.8~5.8 |
Cognitive |
-2.2 (-1.9) |
1.7 (1.8) |
-8.9 (-6.2) |
|
| Affective |
-1.8 (-1.6) |
1.8 (1.8) |
-6.8 (-5.3) |
||
| Conative |
-1.8 (1.1) |
1.9 (2.2) |
-6.6 (-3.0) |
||
| Action |
-1.1 (-1.0) |
1.5 (1.7) |
4.8 (3.4) |
||
| Total |
-1.7 (-1.5) |
1.6 (1.6) |
7.7 (5.4) |
||
|
3 Football Involvement 6 < |
Cognitive |
-2.7 (-2.8) |
1.7 (1.7) |
-10.2 (-9.2) |
|
| Affective |
-1.4 (-1.5) |
2.0 (2.0) |
-4.8 (-4.5) |
||
| Conative |
-1.0 (-1.1) |
1.9 (2.1) |
-3.5 (-3.0) |
||
| Action |
-1.0 (-1.0) |
2.0 (1.9) |
-3.2 (-2.8) |
||
| Total |
-1.5 (-1.6) |
1.6 (1.5) |
-6.2 (-5.9) |
Looking at the results, it was found that there were significant differences among groups in terms of affective and conative loyalty including responses related to Player 1. Specifically, the F-value was calculated as 4.0/5.2(1.4/1.8) and the significance probability was calculated as 0.020/.006(.248/.175). In the case of the Welch and Brown-Forsythe test results, the significance probability of affective loyalty was .030/.020(.301/.251) and the significance probability of conative loyalty was .008/.006(.165/.176). Ultimately, only the results with the responses related to Player 1 included showed a difference. In the case of cognitive and action loyalty, the F-value was 1.0/1.3(1.8/.8) and the significance probability was .385/.281(.170/.439), respectively, indicating that there was no difference among groups. In addition, as a result of analyzing the entire team loyalty measure, the F-value was calculated as 2.4(.8) and the significance probability was calculated as .910(.448), confirming that there was no difference between groups. The derived results are presented in <Table 7>.
Table 7.
Football involvement impact verification Result (One-way ANOVA)
| Aspect | F | p | p(Welch) | p(B-F) |
|---|---|---|---|---|
| Cognitive | 1.0 (1.8) | .385 (.170) | .359 (.151) | .384 (.171) |
| Affective | 4.0 (1.4) | .020 (.248) | .030* (.301) | .020 (.251) |
| Conative | 5.2 (1.8) | .006 (.175) | .008* (.165) | .006 (.176) |
| Action | 1.3 (.8) | .281 (.439) | .340 (.492) | .285 (.442) |
| Total | 2.4 (.8) | .091 (.448) | .121 (.500) | .091 (.450) |
Based on these results with the inclusion of responses of Player 1, post-hoc analysis was conducted in terms of affective and conative loyalty. Tamhane, Dunnett T3, and Games-Howell, which are used when equal variance is not assumed, were all verified. Looking at the results, it was found that there was a significant difference between group 1 (lower 33% of football involvement, <3.5) and group 3 (higher 33% of football involvement, >6). Specifically, in terms of affective loyalty, the results of Tamhane, Dunnett T3, and Games-Howell were .029, .029, and .026, respectively. Moreover, the difference between the means was -1.16, indicating that the difference in loyalty before and after the exposure in the high involvement group was greater. In terms of conative loyalty, Tamhane, Dunnett T3, and Games-Howell verification results were all calculated as .006. Furthermore, the difference between the means of before and after reading the stimulus was calculated as -1.34. Hence, it can be seen that the stimulus has a greater effect on loyalty in the high involvement group than in the low involvement group. Based on the results, H2 was partially supported.
Discussion
Many professional sports teams’ marketing efforts are now geared toward international market expansion—especially Asia. This trend is especially evident within European football teams as they try to leverage their worldwide popularity. Although many marketing operations are undertaken by these teams, the current study aimed at examining the effect of signing athletes who originate from the target market (particularly a national icon with nation-wide popularity) on fans’ loyalty toward the respective team as such method is most approachable and effective for teams. This assumption is supported as fans tend to follow the teams that feature their national athletes (Chadwick, 2007; Mason, 1999). Hypothesis 1 was fully supported, meaning that signing athletes have a positive effect on fans’ all four-stage loyalty (i.e., cognitive, affective, conative, and action) toward the respective team. In other words, when teams sign a player whom fans deem high in value and deem to have a positive image, fans’ loyalty toward the signing team increases. To the knowledge of the authors, extant studies have yet to empirically investigate the effect of athlete signing as a tool for market expansion in the realm of sports marketing literature. The current study fills this gap. These effects can be explained in conjunction with the concept ‘customer equity’. It is related to the provider’s perceived discounted lifetime value of all its customers (Blattberg & Deighton, 1996) and, therefore, is the most reliable equity for deciding long-term value (Lemon, Rust, & Zeithaml, 2001). Major drivers are value, brand, and relationship equity and these drivers are independent and have integration relationships (Lemon et al., 2001). A player’s value can be linked to value equity and player image can be related to relationship equity. Both of which are linked to overall brand equity. Therefore, it can be said that this phenomenon occurred because customer equity formed by consumers on players is transferred to the team that signed the players.
Hypothesis 2 was partially supported as the increase in affective and conative loyalty was proven to be significant including responses related to Player 1. However, if the response related to Player 1 was excluded, there was no significant result. This means that the effect of signing athletes on affective and conative loyalty will be enhanced to fans who are highly involved in football when a player with high perceived value is transferred. These results can be explained through former research. Hupfer and Gardner (1971) showed a significant relationship between product and involvement, which refers to a general level of interest in or concern about a product class. And then more specifically, Liang (2012) provided the results of a positive correlation between consumer product involvement and product knowledge. Looking at the results of the current study, the results showed differences in affective and conative loyalty, when including the response of player 1 (who had a higher perceived value compared to other players in the stimulus material). Previous research, which studied the role of Indian sports celebrity, found that when a sports icon’s image aligns with the country’s culture and political atmosphere, this icon can become a national sports symbol with a spotlight from the public. Furthermore, when this atmosphere is connected with nationalism, the attention from the public can be amplified (Nalapat & Parker, 2005). Existing research shows that the amplification of public interest in sports icons is related to nationalism. Through this, it is possible to explain the moderating effect of involvement in affective and conative loyalty. This is highly related to the emotional aspect of a person that can be linked to patriotism, not mere cognition and actual behavior.
Moreover, a study by Yuksel, McDonald, and Joo (2016) also mentioned that the involvement of consumers is an important part of distinguishing between general CRM(Cause-related marketing) and CRSM(Cause-related sports marketing). In the case of sports consumers who consume sports based on hedonic needs, they have a high level of identification or involvement in the sports categories, sports organizations, and sports clubs. The current study suggests that this acts as a factor influencing the reactions that appear when marketing is executed. The findings of the current study provide notable contributions. In particular, the authors established the vital role of the player signing in improving team loyalty which ultimately triggers revenue increase. From this perspective, the current study fills the gaps in team marketing literature. Based on this, in future studies, the process in which contracts with specific players affect the team's loyalty and the process in which the increased loyalty leads to the actual team's sales can be analyzed in more depth. Furthermore, the authors verified the moderating role of involvement in the aforementioned relationship. It is meaningful not only to verify the effect of a specific player contract on the team but to verify the effect of the individual consumer's characteristics in the occurrence of such effect. Future studies should verify the personal characteristics of consumers, other than loyalty, that may be affected by player signing.
There also are practical implications derived from the current study. First, the results provide and evidence or a basis for deciding transfer fees and salaries of foreign players, especially from potential markets. Players can also benefit from these results as they can appeal to the potential signing team how team loyalty can change through their signature. This can be one of the leveraging methods for players to get better contract conditions and salaries. From the teams’ point of view, they would have many diverse reasons for signing players from potential markets. Following the results of this study, the drivers of customer equity such as value and relationship can influence consumers’ attitude and teams need to consider these factors. Concretely, it is important to identify player’s value and brand equity. Moreover, teams need to consider player characteristics and personal traits to draw long-term success. Secondly, as signing athletes enhance highly involved fans’ affective (liking) and conative (superiority) loyalty, teams can undertake customized marketing efforts (e.g. Facebook post in their language) to enhance their consumer relationship. With these activities, teams can expect revenue increase as global viewership directly affects team revenue through broadcasting rights and sponsorship. Moreover, new media platforms such as Facebook and YouTube viewership also generate revenue. Lastly, In the case of a team, the research results can be used to select target consumers. The results showed that the group with a high level of involvement in football responded more sensitively to the signing of a specific player. Teams can take these results into account when setting up a marketing plan to penetrate overseas markets through signing a specific player.
Conclusion
The purpose of the current study was to examine the role of signing a sports national icon as a tool for market expansion for professional sports teams. In this study, the survey method was used for data collection, and paired t-test and one-way ANOVA were used for data analysis. Looking at the results, there was a difference in team loyalty when participants were exposed to the news that the team signed their national team player. In addition, in the verification of the moderating effect of involvement in football, differences between group 1(lower 33% of football involvement, <3.5) and group 3 (higher 33% of football involvement, >6) were found. Although the results of the current study are consistent and robust, the authors recognize several limitations that must be taken into account when generalizing the results of the current study. The first limitation is that the sports used in the study was football. Thus, the findings may have been influenced by the specific characteristics of football fans, and may be difficult to generalize the results to sports fans in general. Additional samples from different types of sports should be collected in future research to further clarify the effect of player signing on team loyalty.
Another limitation is that the current study focused only on team loyalty as a dependent variable. Although the authors chose loyalty because of its role in fans’ team-related behaviors, future research should examine more consumer purchase behavior aspects such as conversion intention, willingness to pay, and customer lifetime value to more clearly estimate the actual purchase behavior by going one step further from the purchase intention of consumers. In sum, the current study contributes to the body of our knowledge by empirically examining the effect of the player signing on team loyalty. Findings from this research contribute to understanding the effect of the player signing as a team’s global market expansion effort and provides valuable implications. The proposed recommendations derived from the analyses provide important cues for future research.
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