ORIGINAL RESEARCH ARTICLE

The Role of Celebrity and Status in the Performance–Pay Relationship: Evidence from the ‘Big Five’ European Football Leagues

Antonio Giangreco^1,2*, Barbara Slavich^1,2, Alessandro Piazza³, Fabrizio Castellucci⁴, and Cyrus Mohadjer^1
1IESEG School of Management, Paris and Lille, France
²LEM-CNRS UMR 9221, Lille, France
³Jesse H. Jones School of Business, Rice University, Houston, USA
⁴Department of Management and Technology, Bocconi University, Milan, Italy

 

 

Abstract

 

Introduction

The relationship between the compensation level and performance of individuals in organisations has continuously attracted attention from management scholars and has been investigated from a range of perspectives (Chiang & Birtch, 2010; Shin & You, 2017; Wade, Porac, Pollock, & Graffin, 2006). Despite a sizeable literature, there are aspects surrounding the relationship between the two constructs that warrant further investigation. Firstly, the dominant direction of the relationship between pay levels and performance (pay-for-performance) is not so clear-cut when observed over time. In some cases, it has been argued that the opposite relationship exists, especially in some industries such as arts, show business and professional sports, where the performance achieved over a specific period has a stronger impact on the pay levels of the following season (e.g., Montanari, Silvestri, & Bof, 2008; Thrane, 2019). Secondly, the performance–pay relationship is often much more complex, as other mechanisms might intervene to determine the connection between performance and pay levels.

Important among the issues that deserve further attention is the frequent and pervasive occurrence of mismatches between performance and pay. In particular, in overexposed contexts such as arts, show business and professional sports (e.g., Baccarella, Wagner, Kietzmann, & McCarthy, 2018), actors or employees are potentially highly visible to and representative of organisations, and therefore, social media and digital broadcasting might exert strong effects on actors’ global visibility, attracting the attention of large audiences and generating revenue in the process (Scoppa, 2015). Particularly illustrative of this trend in sports is, for example, the fact that in the National Basketball Association (NBA) players’ compensation in the 1999–2000 season was 140 times higher than what it was 30 years before. This remarkable increase in remuneration and the salary differences that exist today among professional players, however, do not appear to have been triggered by significant changes in players’ underlying performance. An inquiry into the nature and boundary conditions of the performance–pay relationship is, therefore, both timely and necessary so as to avert or remedy the detrimental and suboptimal allocation of scarce resources in organisations.

In this study, we argue that while there is generally a positive relationship between the performance of actors and their pay levels (Montanari et al., 2008; Thrane, 2019), the extent to which the two are linked might be moderated by some individual-level intangible assets, such as being a celebrity or having a high status. In the management literature, these latter variables have been associated with a variety of organisational outcomes (Ertug & Castellucci, 2013; Pfarrer, Pollock, & Rindova, 2010; Rindova, Pollock, & Hayward, 2006); however, their role in shaping the link between performance and pay levels has not been thoroughly explored, making further research a priority. Furthermore, we argue that these intangible assets are especially likely to affect the performance–pay relationship, inasmuch as high-status actors, or celebrity actors, tend to be evaluated more positively regardless of their performance (Podolny, 2010) and their conformity to audience expectations (Rindova et al., 2006). Against this backdrop, we seek to better explain why misalignments between performance and pay might occur in organisations. Furthermore, we analyse how such misalignments might be linked to, as well as impact, employee selection strategies adopted by organisations and the strategies that individuals might adopt to negotiate their salaries, for example, by leveraging their visibility and connection with audiences. Based on these arguments, we formulated the following research question: how do the individual intangible assets of celebrity and status influence the relationship between actors’ performance and pay levels?

In response to the above question, we argue that, firstly, individuals who are considered celebrities will naturally draw the attention of audiences to a greater degree than those who are not, thereby generating economic rents through their visibility; for this reason, performance might then become less important in determining the extent of their compensation by organisations. Therefore, we expect celebrity to negatively moderate the performance–pay relationship. Secondly, because status is widely considered a proxy for quality, high-status players tend to not only be less exposed to scrutiny (Podolny, 1993) but also more likely to be awarded higher salaries, irrespective of their performance (Ertug & Castellucci, 2013). Status hierarchies are, in fact, characterised by flows of deference directed towards the top (Piazza & Castellucci, 2014), and as a result, the contributions of high-status individuals are typically thought of as being more valuable. Therefore, we argue that status will also negatively moderate the performance–pay relationship.

The performance–pay relationship and the moderating role of individual status and celebrity explored in this study are bound by certain characteristics of specific organisations, industries and sectors. Our theorisation might be relevant in specific settings, such as professional sports, cultural industries and the employment market at the executive level, but not necessarily in conventional settings, such as in relation to firms’ usual employment contracts. Indeed, in these specific contexts or circumstances, actors or employees are potentially highly visible and representative of organisations in their capacity to generate emotional responses and attract attention from large audiences (Rindova et al., 2006). These industries are also characterised by a great number of people who know and pay attention to the actions of actors or firms; firms are likely to generate emotional responses in audiences; actors serve as vivid examples of important changes and extraordinary actions in the industry; and media play a key role in attributing favourable qualities to some actors (Rindova et al., 2006).

The empirical setting for this study is the top five (‘Big Five’) European football leagues. Professional sports, and specifically European football, appear to be an appropriate context in which to understand the effect of celebrity and status on the relationship between performance and pay. Indeed, football is one of the world’s most popular sports. It is a labour-intensive industry characterised by skilled individuals who, by also leveraging their status and celebrity, play a decisive role in the achievement of organisational objectives (Carmichael, McHale, & Thomas, 2011; Tiedemann, Francksen, & Latacz-Lohmann, 2011). Moreover, despite marked salary differences among different roles, there has been evidence to show that one of the main drivers of a player’s salary is individual performance (Dobson & Goddard, 2011). Nevertheless, there seems to be the problem of wage inequality among players (Della Torre, Giangreco, Legeais, & Vakkayil, 2018), and differences in performance do not seem to be the sole explanation (Dobson & Goddard, 2011), which makes the selected setting particularly relevant for our research. Our study contributes to the literature on both compensation and intangible assets by showing that if pay levels depend on actors’ performance, then celebrity and status might act as a substitute for performance, especially when organisations need to maintain high levels of attention and use high status as a substitute signal for quality.

The remainder of the article is structured as follows. We first present the theoretical framework and the arguments supporting our hypotheses. We then describe the research context and methods. We conclude by discussing our findings and presenting both the theoretical and managerial implications of the study, along with some reflections on the generalisability of our results to other business settings.

Theoretical background

Compensation in organisations and the performance–pay relationship

Extant studies on compensation have shown that organisations typically access the labour market, where they offer salaries and other intangible forms of remuneration in exchange for employees’ participation and efforts (Coleman, 1990). Indeed, according to marginal productivity theory, “work is compensated in proportion to its contribution to the organization’s production objectives” (Milkovich, Newman, & Gerhart, 2014, p. 684). Compensation schemes work towards several mutually interconnected objectives (Della Torre, Giangreco, & Maes, 2014), and their primary goal is to reward good performance to create a reinforcement mechanism between behaviours and rewards, making it more likely that the same behaviour will be repeated in the future, as posited by perspectives such as operant conditioning (Skinner, 1953) and expectancy theory (Vroom, 1964). Another goal of compensation schemes is to establish a sense of equity among individuals. As employees compare what they and others receive in exchange for work in an organisation (Adams, 1963), it is important to strive for balance, which can in turn enhance employee motivation (Gerhart, Rynes, & Fulmer, 2009). Moreover, from an agency theory perspective in organisational studies (Conlon & Parks, 1990; Eisenhardt, 1988, 1989), compensation systems must also reconcile the different demands of organisational stakeholders, such as management (the principals) seeking to minimise agency costs, including remuneration, and employees (the agents) seeking to maximise costs through salary and perks (Pepper & Gore, 2015), with the aim of ensuring both fairness and effective use of resources.

Although compensation schemes may vary depending on the type of organisation, job level and type of work, the dominant view of the pay-for-performance approach is that setting-specific reward systems determine the expected levels of performance from individuals (Milkovich et al., 2011). Following this stream of research, it can be argued that organisations make important choices in the design of their pay systems, and these choices have implications for organisational performance (Brown, Sturman, & Simmering, 2003; Gerhart & Milkovich, 1990; Nyberg, Pieper, & Trevor, 2016), contribute to the behavioural drive of individual performance and support the achievement of organisational objectives (Milkovich et al., 2011).

Some scholars, however, have raised doubts about the validity and generalisability of the pay-per-performance approach (Gerhart & Fang, 2014) and have variously questioned the real influence of money in motivating people. This might be especially relevant in public-facing industries where actors are potentially highly visible and representative of organisations, and thus other variables might come into play in explaining pay levels. For example, in professional sports – which is the context of our research – some scholars have taken into account non-field elements that affect the choice of actors’ pay levels (Carlsson-Wall, Kraus, & Messner, 2016) or the correct estimation of their value and pay (Risaliti & Verona, 2012). In a similar way, a few scholars have considered the perspective of the superstar effect (Lucifora & Simmons, 2003) and used talent and popularity proxies to better explore the relationship between performance and pay, although with contrasting results (e.g., Franck & Nueshc, 2008; Lehmann & Schulze, 2008).

The above reasoning shows that the relationship between the two constructs might be more pronounced and controversial, particularly in industries and contexts in which a great number of people pay attention to the actions of actors and media play a key role in attributing favourable qualities to some actors (Rindova et al., 2006). For instance, in a study of professional football, Della Torre et al. (2018) found the relationship between past and future performance to be partially mediated by salary related to the latter, creating a self-reinforcing dynamic. This means not only that pay might impact performance, as posited by much of the literature on the topic, but also that, over time, performance might also impact compensation levels (Thrane, 2019). In fact, during the year, individuals typically receive t+1 levels of pay as recognition of the performance delivered in year t (Montanari et al., 2008). Based on this perspective, the relationship between the two constructs shows a path in which only performance affects pay levels (Thrane, 2019). Building on this line of argument, we suggest that in organisational settings, individuals’ performance is predictive of their pay levels; we thus formulate the following as our baseline hypothesis:

H1: The performance of individuals (in year t) is positively related to their pay level (in year t+1).

Building on the above reasoning and this baseline hypothesis, we argue that the relationship between performance and pay warrants further research so as to better understand the source of potential misalignment between the two constructs. In the remainder of the article, we show that the intangible socially evaluated characteristics of specific actors, such as celebrity (Rindova et al., 2006) and status (Castellucci & Ertug, 2010), are likely to affect the relationship between performance and pay. These intangible assets influence the way in which an actor’s contribution is framed, while also providing organisational value beyond tangible measures of performance. Indeed, other things being equal, high-status individuals are generally thought to provide more valuable inputs to organisations, while celebrity is associated with greater organisational visibility and greater ease in accessing resources (Salancik & Pfeffer, 1978). In the following sections, therefore, we elaborate on the reasons why celebrity and status are especially likely to influence the link between performance and pay.

The role of celebrity in the performance–pay relationship

Organisations’ intangible assets, particularly the social approval assets (e.g., celebrity, reputation and status) whose value is derived from collective and shared perceptions, have attracted considerable research attention over the past years (Pfaffer, Pollock, & Rindova, 2010; Pollock, Lashley, Rindova, & Han, 2019; Rindova et al., 2006). Among social evaluations, celebrity is generally taken to represent both a ‘high level of public attention’ (visibility) and the positive emotional resonance generated by some actors (Rindova et al., 2006, p. 51). This concept is primarily based on emotional evaluations, which have more influence than the rational and moral evaluations of other intangible assets (Pollock et al, 2019). Celebrity has its foundation in the sociology of mass media and, like other intangible assets, determines an organisation’s willingness to establish exchange relationships with a particular individual or firm (Lounsbury & Glynn, 2001; Rindova & Fombrun, 1999). Celebrity, not to be confused with reputation (see Zavyalova, Pfarrer, Reger, & Hubbard, 2016), is defined by the strong emotional responses it evokes from the public (Rindova et al., 2006) and refers to the “attention-getting, interest-riveting and profit-generating value” (Rein, Kottler, & Stoller, 1987, p. 15) associated with the names of some individuals. According to this definition, celebrity is an attribute of an individual’s relationship with an audience, more than an individual-level characteristic (Rein et al., 1987). Thus, the level of social approval linked to celebrity depends on the emotional responses, excitement, engagement and positive affect that an individual evokes (Pfarrer et al., 2010).

Individuals who have achieved celebrity status are highly visible, attract public attention and are expected to meet audiences’ need for identification, gossip and fantasy (Rindova et al., 2006). They are the result of a social construction process developed through the media and social networks, which dramatise their counter-normative behaviours to stimulate audience engagement and identification (Pollock et al., 2019). Media play a key role in directing audiences’ attention towards particular actors through dramatic effect, emphasising their unusual actions and distinctive characteristics. Thus, the attention that celebrities generate might not necessarily refer to performance-related aspects. For instance, to increase an individual’s appeal and engage audiences, media might select, highlight and sometimes manipulate information about an individual’s personality or personal life, generating emotional responses through identification or admiration (McCracken, 1989).

Some studies have explored the role of intangible assets in the field of highly exposed settings, such as professional sports, and individuals, such as Chief Executive Officer (CEOs) (e.g., Wade et al., 2006). For example, Ertug and Castellucci (2013) studied the role of reputation and status in basketball to explain organisational value. Other scholars have explored the role of celebrity in generating revenue for football organisations (Garcia-del-Barrio & Pujol, 2007) and highlighted that, beyond performance, celebrity players generate off-field revenue because of their popularity. This creates intangible and indirect organisational economic advantages through merchandising products, broadcasting rights and fan attendance (Garcia-del-Barrio & Pujol, 2007). Thus, when clubs evaluate players’ contributions, they take into consideration not only their performance but also their capacity to generate revenue via fan identification or admiration.

Therefore, we argue that when organisations evaluate actors’ contribution and determine their pay levels, they take into consideration not only these actors’ performance but also their capacity as celebrities to generate revenue. Such benefits can substitute for performance considerations in determining pay levels, thereby loosening the link between performance and pay. Insofar as celebrity generates an economic contribution that is valuable to the organisation, performance will become less relevant in explaining an actor’s salary, and actors who benefit from celebrity will not need to perform as impressively as others to achieve a given pay level. Overall, we predict that for celebrity actors, the relationship between performance and pay should become weaker. Therefore, we propose the second hypothesis:

H2: The celebrity of an actor negatively moderates the performance–pay relationship so that, for higher levels of celebrity, the impact of performance on pay will be lower.

The role of status in the performance–pay relationship

Status has been defined as the perceived quality of a producer in relation to its competitors or similar others (Piazza & Castellucci, 2014; Podolny, 1993; Podolny & Stuart, 1995). This concept “invokes the imagery of a hierarchy in which an individual’s location in that hierarchy shapes others’ expectations and actions toward the individual and thereby determines the opportunities and constraints the individual confronts” (Podolny, 2010, p. 11). High-status individuals enjoy several benefits, such as greater access to capital, faster growth, higher prices for their products, privileges independent of their performance and greater effort from their exchange partners (Benjamin & Podolny, 1999; Castellucci & Ertug, 2010; Podolny, 1993; Podolny, Stuart, & Hannan, 1996; Washington & Zajac, 2005). Essentially, in line with the Matthew effect (Merton, 1968), high-status individuals receive greater rewards than other actors for performing similar tasks (Merton, 1968, 1995; Podolny, 1993) and continue to enjoy such privileges independently of their performance and merit (Washington & Zajac, 2005).

When discussing the concept of status, Washington and Zajac (2005) argued that once status is acquired, it tends to remain stable, even in the face of declining quality or performance. To put this in general terms, once an individual achieves a high status, the quality of their products will be under less scrutiny, compared to the products of lower-status actors (Podolny, 1993). Research has shown that because of reduced scrutiny, high-status actors are less likely to conform to social norms (Phillips & Zuckerman, 2001), that start-ups assemble more high-status venture capitalists to increase their Initial Public Offering (IPO) evaluation (Chen, Hambrick, & Pollock, 2008) and that stock analysts will unquestionably follow firms’ coverage of high-status analysts (Rao, Greve, & Davis, 2001). Another stream of research has shown that high-status actors might be subject to increased scrutiny following wrongdoings. For instance, high-status members of the House of Commons of the British parliament are more likely to receive more press coverage during a scandal (Graffin et al., 2013), and ambiguous transgressions are perceived as intentional and punished if an actor’s status is based on dominance rather than prestige (Kakkar, Sivanathan, & Gobel, 2019). Therefore, insofar as they are not involved in wrongdoings and status is based on prestige, the general finding coming from the status literature is that high-status actors are subject to less scrutiny than their low-status counterparts. Consequently, insofar as we do not either consider wrongdoings of actors nor we consider status based on dominance, we might well expect past demonstration of quality for high-status actors not be as closely scrutinised as it is for low-status ones.

Our first baseline hypothesis suggests that organisations observe past performance and determine an individual’s pay based on it. However, as high-status actors’ performance is less closely scrutinised, it is possible to argue that organisations will weigh less the performance of those high-status actors when determining their pay than they do for low-status ones. Since these individuals achieved a high status, their performance will be under less scrutiny and will become less relevant in explaining their salary level. As in the case of the previous hypothesis, this does not mean that higher-status individuals will receive less pay for equal performance. Rather, what we are theorising is that status functions as a moderator of the main effect of performance on pay. In other words, the performance of high-status individuals is less relevant in determining these individuals’ pay, and the association between performance and pay will be weaker for high-status actors. Therefore, we hypothesise as follows:

H3: The status of an actor negatively moderates the performance–pay relationship so that, for higher-status levels, the effect of performance on pay will be lower.

Methods

Empirical setting

We tested our hypotheses on a data set of European football players from the very popular Big Five leagues (the English Premier League, Spanish La Liga, Italian Serie A, German Bundesliga and French Ligue 1). In recent research on football, such as those done by the Swiss-based CIES Football Observatory, the Big Five are often used as a research context.

Organisational performance in football, as in many team-based professional sports, while characterised by high levels of interdependency among players (Lechner & Gudmundsson, 2012), depends on the quality of the individual performance of each player. This is reflected in the fact that, when pay levels are high, negotiation is conducted at the individual level. Pay is usually negotiated after a transfer from one team to another, with players aiming to agree on contracts of maximum length, which is 5 years for the five leagues analysed. However, when players perform particularly well or beyond expectations, their pay levels are often increased (Montanari et al., 2008), or if they are nearing the end of their career, a temporal extension of their contract is usually the case. Conversely, clubs have the tendency to satisfy the wishes of players if they predict that their value will increase over time, especially if the players are in the early stages of their careers. This is habitually done to prevent promising players from having their contract expired, after which they could move freely to another club under the more favourable condition of obtaining higher pay levels.

Evidence from football clubs seems to suggest that players’ pay levels are not always due to their performance and are typically an additional function of exposure and status. For example, two players, Eder and Carlos Bacca, in season 2014–15 were shown to have several commonalities: both scored the same individual performance of 7.01; both played in the same roles as strikers; both played in top Italian clubs, Inter Milan and AC Milan, respectively, and they were both in their late 20s, aged 28 and 29, respectively. However, the difference in both Facebook likes of 30,000 and 215,000 (our measure of celebrity), respectively, and the number of matches played for their national team of 6 and 22 (our measure of status), respectively, produced major differences in their respective salaries of 2 and 7 million euros, respectively, in the following season. Taken together, these arguments show that intangible characteristics such as status and celebrity might interfere with the link between key player/individual-related constructs, thereby justifying further research.

Dependent and independent variables

Our data set covered individual players who are active within the Big Five European football leagues, salary information, technical indicators of player performance and indexes of popularity and status. Our sample was limited to players who, at a minimum, had taken part in the average number of matches played in that specific league, which was 19 championship matches (17 for Germany) and 1,100 min (1,025 for Germany) of play per year. In this way, the sample only comprised footballers whose performance could be tracked over a significant time period, avoiding the inclusion of occasional players whose presence might have biased the analysis, such as youths often summoned to play a few matches with the first team when needed. Bucciol, Foss and Piovesan (2012) suggested this distinction between stable and occasional players in their study on Serie A. Not only is the performance of occasional players likely to be idiosyncratic, but the degree to which performance can be used to establish their compensation level is also unclear, potentially creating problems for our analysis. Moreover, to be included in our data, players must have played in one of the Big Five leagues for two consecutive seasons, although not necessarily for the same team. Our data set included a total of 942 complete observations of 471 individual players¹, whose salaries we tracked during the 2015–2016 and 2016–2017 seasons, and performance was measured during 2014–2015 (to study the impact on salaries in 2015–2016) and 2015–2016 (to study the impact on salaries in 2016–2017). Our data set was, thus, a short panel with T = 2. Descriptive statistics and pairwise correlations for all our variables are reported in Appendix 1.

Dependent variable

The dependent variable for our study was the gross absolute salary of players (in euros), player salary, during season t; this variable was then logged for use in our models. Our primary sources for data collection were national newspapers, such as MARCA (Spanish Liga), Kicker (German Bundesliga), Sportune (French Ligue 1), La Gazzetta dello Sport (Italian Serie A) and the website Totalsportek (English Premier League). We used the gross, rather than the net, salary figure because tax policies differ substantially from one country to another, and it is arguably a better measure of clubs’ willingness to pay for the services offered by a player.

Independent variable

Player performance was measured through Whoscored, one of the largest online databases that covers football information on over 150,000 players from all the European leagues; it has previously been used in other studies (e.g., Liu, Giménez, Gómez, & Lago-Peñas, 2015; Sgro & Lipoma, 2016). Whoscored keeps track of a variety of individual and team performance indicators, gathering data on gameplay aspects such as clearances, tackles, percentage of passes completed, etc., using a proprietary algorithm to rate players’ performance in real time during the course of a game. For our study, we used individual performance ratings generated by Whoscored, which are the result of over 200 indicators used to produce ratings of a player’s performance over the same season on a scale from 0 to 10, weighted according to their influence within each game. Generally, it is considered difficult to capture all aspects of an individual’s performance in football; nevertheless, this indicator has been used as a highly relevant measure of a player’s performance because of its pronounced analytical shape, its common scale for the Big Five leagues and its adjustment to a player’s role and position.

Moderating variables

Celebrity

Following Mohammadi, Farahbakhsh and Crespi (2017) and Nelson-Field, Riebe and Sharp (2012), we measured celebrity by counting and logging how many ‘likes’ each player received by fans in the previous year on their official public Facebook page. These studies showed that professional users, such as celebrities, create Facebook pages to interact with fans and that Facebook users attribute ‘likes’ to specific celebrities and the contents they admire, thereby determining the popularity of a piece of content or attributing the status of celebrity to an actor. Celebrity has been previously defined as a combination of high levels of public attention and positive emotional responses from audiences. Building on previous studies (Pfarrer et al., 2010) that have used both components, we argue that social media platforms, such as Facebook, allow the summarising of these two dimensions: indeed, they likely contain dramatic narratives that connect followers emotionally to players while simultaneously highlighting public attention through follower count. While social media-based measures of popularity are still gaining traction in the organisational literature, there is growing evidence that as celebrity shifts from television and print media to the Internet (Lazer & Radford, 2017), such measures will only increase in prominence in the coming years across different industries (e.g., Choi & Berger, 2009; Lewis, Gray, & Meierhenrich, 2014; Marwick & Boyd, 2011; Mathys, Burmester, & Clement, 2016).

Status

For our second moderating variable, player status, we leveraged a cumulative count of the number of times a player had been invited to play for his country’s national team, up to and including the previous season. Our choice is consistent with measures that have been commonly used in the status literature (Piazza & Castellucci, 2014; Washington & Zajac, 2005). Indeed, because status is assumed to be rooted in flows of deference and respect from other social actors within the same field, awards and nominations could be seen as tangible manifestations of such deference (Ertug & Castellucci, 2013; Kim & King, 2014). Similarly, having been selected for the national team could be seen as a useful proxy for status insofar as only a limited number of positions are available and national team members are given great respect by their peers. Finally, because performance, status and celebrity were found to be highly correlated, we orthogonalised them by means of a modified Gram–Schmidt procedure, as implemented through the orthog command in STATA, which made them independent, thus avoiding multicollinearity issues. This procedure has been used to obtain measures that capture variance which could not have been explained by a linear relationship with other variables (see, e.g., Hiatt, Sine, & Tolbert, 2009; Pollock & Rindova, 2003).

Control variables

Firstly, we controlled for player age, given that younger players often receive higher valuations than older ones (Della Torre et al., 2014, 2018; Torgler & Schmidt, 2007). Since different national teams have different levels of prestige, a fact reflected in the Fédération Internationale de Football Association (FIFA) annual ranking of national teams, our models included a variable for national team status, which we operationalised as the equivalent of the national team’s position in the FIFA ranking for each given player. Moreover, given that the resulting variable was highly skewed, we log-transformed it. We also included the dummy variable, Team Champions League participation, as participation in prestigious international tournaments, such as the Union of European Football Associations (UEFA) Champions League, as it might increase players’ visibility (0 = no participation; 1 = participation). To control for teams’ financial constraints, and considering that larger, wealthier teams can pay higher salaries to their players, we included the variable team market value as a proxy for team budget; this was collected from the website Transfermarkt, a popular website specialising in attributing a value to each player, which has been referenced in other studies (e.g., Franck & Nuesch, 2008; Gerhards & Mutz, 2016; Kiefer, 2014; Majewski, 2016; Thrane, 2019). This measure was considered a reliable proxy of value because “… in the context of multiyear contracts where teams often face the decision whether to sell a player or not to a different team, Transfermarkt values not only capture the explicit cost to the player’s team, but also the implicit cost that is associated with keeping a player on a team rather than selling it” (Green, Lozano, & Simmons, 2015, p. 35). Moreover, as a player’s salary might also depend on the length of his remaining contract, we also included years of contract remaining as a variable. In addition, to account for the fact that teams might be inclined to provide better compensation to players who perform well in particular areas (defence, offense or facilitating game flow), we constructed several control variables: (1) the promotion score, that is, the number of goals and assists divided by two and attributed to the player in the previous season; (2) the prevention score, that is, the sum of interceptions and clearances and (3) the percentage of completed passes, a proxy for better ‘team players.’ Finally, we added season dummies to control for time-dependent effects and position dummies to control for roles.

Results

Table 1 presents the results of our panel ordinary least squares (OLS) models, with logged player salary as the dependent variable. Model 1 was limited to control variables and moderators, while Model 2 added position and season dummies. We can see that both a player’s high status and celebrity had a positive effect on pay levels, indicating that popular and high-status players tend to receive better remuneration. Unsurprisingly, team market value also showed a positive effect because wealthier teams tend to pay their players more. Additionally, players whose contracts had more years remaining had registered higher salaries, presumably due to both salary inflation and holding greater bargaining power in comparison with free agents and players whose contracts were about to expire. Model 3 added performance, whose effect was shown to be positive and significant, indicating support for Hypothesis 1. The estimate suggests that a standard deviation increase in player performance from the previous season results in a 12.9% increase in compensation. Model 4 added the first interaction effect found between celebrity and performance. The coefficient was negative and significant, indicating that the effect of performance on pay was indeed weaker for players with more celebrity. Hypothesis 2 has, therefore, been supported. Using the coefficients estimated in Model 4, the marginal effect of the interaction is depicted graphically in Figure 1. Figure 1 indicates that for players with the least celebrity, performance had an effect on compensation, which exceeded 20% (for a standard deviation increase in performance); conversely, for the most famous players in the sample, the extent of the effect was less than 10% in magnitude for a standard deviation increase in performance and was statistically indistinguishable from zero.

Table 1. Panel OLS regression results for logged player salary

Variables	(1)	(2)	(3)	(4)	(5)
	Model 1	Model 2	Model 3	Model 4	Model 5
Years of contract remaining	0.111***	0.111***	0.106***	0.105***	0.104***
	(0.015)	(0.015)	(0.015)	(0.015)	(0.015)
National team status (log-transformed)	0.012	0.027	0.047	0.046	0.050
	(0.122)	(0.120)	(0.117)	(0.117)	(0.118)
Player status (orthogonalised)	0.497***	0.494***	0.519***	0.514***	0.518***
	(0.024)	(0.025)	(0.026)	(0.026)	(0.026)
Team Champions League participation (dummy, orth.)	0.375***	0.381***	0.396***	0.398***	0.400***
	(0.025)	(0.025)	(0.025)	(0.025)	(0.025)
Player age	-0.008	-0.011	-0.008	-0.009	-0.009
	(0.008)	(0.008)	(0.008)	(0.008)	(0.008)
Player celebrity (orthogonalised)	0.228***	0.213***	0.225***	0.227***	0.226***
	(0.022)	(0.023)	(0.023)	(0.023)	(0.023)
Promotion score	0.026***	0.022***	0.003	0.006	0.006
	(0.003)	(0.004)	(0.005)	(0.005)	(0.005)
Prevention score	0.002	0.010	-0.018	-0.018	-0.019
	(0.009)	(0.012)	(0.013)	(0.013)	(0.013)
Percentage of completed passes	0.004	0.006	0.004	0.004	0.004
	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)
Team market value (previous season, orthog.)	0.214***	0.217***	0.229***	0.231***	0.233***
	(0.025)	(0.025)	(0.027)	(0.027)	(0.027)
Season dummies	No	Yes	Yes	Yes	Yes
Position dummies	No	Yes	Yes	Yes	Yes
Performance (previous season, orthog.)			0.129***	0.129***	0.131***
			(0.026)	(0.025)	(0.025)
Performance (previous season, orthog.) x Player status (orthog.)				-0.025+	-0.027*
				(0.014)	(0.014)
Performance (previous season, orthog.) x Player celebrity (orthog.)					-0.026*
					(0.013)
Constant	-0.542	-0.334	0.063	0.043	0.050
	(0.393)	(0.419)	(0.413)	(0.415)	(0.413)
Observations	840	840	840	840	840
R-squared (overall)	0.700	0.707	0.718	0.719	0.720
Number of players	464	464	464	464	464
Robust standard errors are in parentheses. OLS, ordinary least squares. *** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.1

 

Figure 1. Interaction effect between player celebrity and performance

Finally, Model 5 represents our full model, which includes our second interaction effect, that between status and performance, whose coefficient was also negative and significant (Figure 2). Support for Hypothesis 3 was shown to corroborate the idea that the effect of performance on pay was weaker for high-status players. Using the coefficients estimated in Model 5, the marginal effect of the interaction is depicted graphically in Figure 3. Here, the effect of a one-standard deviation increase in performance on pay varied from about 15% for the lowest status players to less than 5% for the highest status players, with the latter effect being – once again – statistically indistinguishable from zero.

Figure 2. Test of moderation hypotheses

 

Figure 3. Interaction effect between player status and performance

Robustness checks

To assess the robustness of our results to alternative specifications, we carried out two distinct robustness checks, reported in Tables 2 and 3. In Table 2, we tested the robustness of our findings by including league dummies to control for time-invariant pay heterogeneity across national leagues; to this end, we compared our full model in Table 1 (Model 5), with the equivalent model containing added league dummies (Model 6). The results broadly confirm our pattern of findings as far as the sign and magnitude of coefficients were concerned, while falling short of conventional significance thresholds. In Table 3, we tested whether our effects might be driven by extreme performers – that is, players whose performance ratings were farthest from the mean. To this end, we re-ran our models and excluded from the sample those players whose performance ratings were at least two standard deviations above and below the sample mean. The results shown in Table 3 once again confirm the pattern of results, as far as the magnitude and sign of the coefficients were concerned, while falling short of conventional significance thresholds. Overall, our robustness checks suggest that our results might be partly driven by extreme performers and league-specific dynamics, something that further research should ideally explore.

Table 2. Robustness check with league dummies

Variables	Model 5	Model 6
Years of contract remaining	0.104***	0.098***
	(0.015)	(0.015)
National team status (log-transformed)	0.050	0.075
	(0.118)	(0.121)
Player status (orthogonalised)	0.518***	0.472***
	(0.026)	(0.027)
Team Champions League participation (dummy, orth.)	0.400***	0.402***
	(0.025)	(0.024)
Player age	-0.009	-0.004
	(0.008)	(0.008)
Player celebrity (orthogonalised)	0.226***	0.208***
	(0.023)	(0.023)
Promotion score	0.006	0.004
	(0.005)	(0.006)
Prevention score	-0.019	-0.028*
	(0.013)	(0.014)
Percentage of completed passes	0.004	0.006
	(0.004)	(0.004)
Team market value (previous season, orthog.)	0.233***	0.187***
	(0.027)	(0.025)
Season dummies	0.014	0.016
	(0.020)	(0.020)
Position dummies	-0.388***	-0.431***
	(0.098)	(0.092)
League dummies	No	Yes
Performance (previous season, orthog.)	0.131***	0.135***
	(0.025)	(0.025)
Performance (previous season, orthog.) x Player status (orthog.)	-0.027*	-0.023
	(0.014)	(0.015)
Performance (previous season, orthog.) x Player celebrity (orthog.)	-0.026*	-0.021+
	(0.013)	(0.013)
Constant	0.050	-0.174
	(0.413)	(0.393)
Observations	840	840
Number of players	464	464
R-squared (overall)	0.720	0.760
Robust standard errors are in parentheses. *** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.1

 

Table 3. Robustness check excluding extreme performers

Variables	Model 7	Model 8	Model 9	Model 10	Model 11
Years of contract remaining	0.104***	0.104***	0.101***	0.101***	0.100***
	(0.016)	(0.016)	(0.016)	(0.016)	(0.016)
National team status (log-transformed)	0.050	0.063	0.075	0.068	0.074
	(0.133)	(0.130)	(0.127)	(0.128)	(0.130)
Player status (orthogonalised)	0.495***	0.492***	0.515***	0.508***	0.511***
	(0.025)	(0.025)	(0.026)	(0.027)	(0.027)
Team Champions League participation (dummy, orth.)	0.369***	0.376***	0.388***	0.391***	0.392***
	(0.025)	(0.025)	(0.025)	(0.025)	(0.025)
Player age	-0.008	-0.011	-0.009	-0.010	-0.010
	(0.008)	(0.008)	(0.008)	(0.008)	(0.008)
Player celebrity (orthogonalised)	0.229***	0.216***	0.225***	0.226***	0.224***
	(0.023)	(0.023)	(0.024)	(0.024)	(0.023)
Promotion score	0.030***	0.024***	0.008	0.009	0.010
	(0.004)	(0.004)	(0.006)	(0.006)	(0.006)
Prevention score	0.001	0.007	-0.017	-0.017	-0.018
	(0.009)	(0.012)	(0.014)	(0.014)	(0.014)
Percentage of completed passes	0.005	0.007	0.005	0.005	0.005
	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)
Team market value (previous season, orthog.)	0.217***	0.220***	0.229***	0.230***	0.232***
	(0.026)	(0.026)	(0.028)	(0.028)	(0.028)
Season dummies	No	Yes	Yes	Yes	Yes
Position dummies	No	Yes	Yes	Yes	Yes
Performance (previous season, orthog.)			0.114***	0.113***	0.113***
			(0.030)	(0.030)	(0.030)
Performance (previous season, orthog.) x Player status (orthog.)				-0.023	-0.027
				(0.018)	(0.018)
Performance (previous season, orthog.) x Player celebrity (orthog.)					-0.030+
					(0.017)
Constant	-0.657	-0.407	-0.069	-0.072	-0.070
	(0.404)	(0.428)	(0.425)	(0.427)	(0.425)
Observations	803	803	803	803	803
Number of players	460	460	460	460	460
R-squared (overall)	0.679	0.687	0.696	0.696	0.698
Robust standard errors are in parentheses. *** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.1

Discussion

This study of a professional football setting shows that celebrity and status play a key role in the relationship between performance and pay by negatively moderating the link between them. In the following sections, we discuss the potential implications of our study for theory and practice and the generalisability of the results to other business contexts.

Theoretical contributions

At a baseline level, this study corroborates the existence of a direct link between individual performance and pay in certain public-facing contexts (Montanari et al., 2008; Thrane, 2019), besides the well-established logic of pay-for-performance. However, the main contribution comes from presenting this relationship as a function of contingent factors that temper its strength. Indeed, an actor’s worth – and ultimately pay level – might depend not only on his or her direct contribution to organisational performance but also on other indirect variables, such as celebrity or status, that moderate the direct contribution. In other words, this work shows that there are boundary conditions on the direct effect of performance on pay and that these boundaries are determined by the level of celebrity and status of the focal actor. This is especially true for industries that are characterised by the presence of a great number of people who know about and pay attention to the actions of actors or firms, firms or actors that are likely to generate emotional responses in audiences, actors who serve as vivid examples of important changes and extraordinary actions in the industry, and media that play a key role in attributing favourable qualities to some actors (Rindova et al., 2006). Secondly, by disentangling the differential effects of the two constructs of celebrity and status, this work contributes to the literature on intangible assets (Pfarrer et al., 2010; Pollock et al., 2019; Rindova et al., 2006). While previous research has mainly focused on the impact of intangible assets on organisational outcomes, in this study, we linked these assets to individuals’ compensation and showed that the emphasis on performance might be diminished under conditions of celebrity or high status.

With regard to the former, this work contributes to studies on celebrity (e.g., Wade et al., 2006; Zavyalova et al., 2016) by shedding new light on a concept that is relatively unknown compared to the related constructs of reputation and fame (Sorenson, 2014). In line with previous research, we consider celebrity as a distinct, intangible asset based on a combination of high levels of public attention and emotional evaluation (Pollock et al., 2019), and our contributions have highlighted its complementarity with performance in determining pay levels. However, organisations need to reach organisational performance, and as such, they might value individuals who can provide resources that allow them to reach this outcome. Moreover, organisations that need to maintain high levels of attention (Pfarrer et al., 2010) might attribute greater value to an individual’s celebrity. In general, we have shown that celebrity in itself can be valuable to organisations, as it makes the actual performance of the actors less relevant in determining their worth.

Our study also contributes to research on status (Piazza & Castellucci, 2014; Podolny & Phillips, 1996) by providing additional empirical evidence concerning the decoupling effect of status on the relationship between performance and pay. The extant literature on the role of status in organisational settings suggests that, because it is more visible and stable than performance, it is often factored into the process through which an actor’s value is determined. This is in line with Ertug and Castellucci’s (2013) study on the NBA, which shows that when status increases, the value of a player depends less on his/her reputation. Similarly, we have posited a moderating effect whereby high-status actors’ pay will depend more on their status level than on their actual performance.

Finally, this study contributes to the literature on social evaluations. Despite knowing a great deal about how social evaluations, such as reputation, status, celebrity or stigma, affect actions, market outcomes, firm outcomes and performance, there is still confusion about the actual differences between these constructs. In a recent article, Pollock and colleagues (2019) called for more studies, including more social evaluation constructs to disentangle the differential effects of these constructs. For instance, Hubbard et al. (2018) compared the effect of status and celebrity on post Initial Public Offering (IPO) strategic alliance formation and found that celebrity is an interpretive frame that shapes how information is perceived, whereas status does not help in framing the analytical aspects of technical information. Deploying both of these constructs, this study found that both celebrity and status help in shaping the perceived worth of an actor by reducing the effect that observable performance has on an actor’s salary. The differential results might be due to the differences in the type and complexity of the information being framed, which suggests that the effects of different evaluation constructs are not universal; rather, they are context-dependent.

Managerial implications

Several interesting managerial implications can be derived from the findings of this study, both for individuals and organisations. The results of this study might serve to warn organisations about the distortive role that status and celebrity can play in the performance–pay relationship. Firstly, the fact that an actor is selected and compensated by an organisation based partly on his or her status is expected – status is, to some degree, reflective of underlying quality. However, organisations should also ensure that actors’ current performance is correctly assessed so as to maintain a rational relationship between status and salary. Secondly, a similar concern emerges because celebrity might also play a role in affecting pay levels. Actors in different contexts are exposed to high levels of public attention, for example, professional players from well-known clubs, CEOs in different business settings or creative directors in industries such as film and fashion. As previously noted, this public attention is not always linked to actors’ job-related performance; it is often related to their overall lifestyle and communication, mirrored in their social connections, power within their networks and media presence. Thus, organisations should be aware that actors considered for their celebrity might be hired not only for their contribution to job-related performance but also for the attention that they might bring to the organisation. Such attention might, in turn, result in higher revenues for organisations which might be willing to pay higher salaries to actors who do not necessarily directly affect organisational performance through their individual performance.

These results should propel managers to better frame and manage the performance–pay mechanism in alignment with the organisational and financial objectives of their company. If it is recognised that the labour market in some contexts is not fully transparent, organisations should improve how they isolate the components of an actor’s contribution in terms of performance as well as through the lens of celebrity and status.

If we interpret our results from the point of view of individual actors, it seems that in order to maximise their salary, one of the strategies that these actors might adopt is to try to become more popular through social media and in the press, in general, in order to generate identification processes and emotions with the public that might lead to great attention. Moreover, our results on celebrity are particularly relevant not for the best performers, who can still obtain high levels of compensation, but for average actors who, through the professional management of social media, could obtain higher compensation. Unlike status, which is essentially more stable and difficult to achieve (Piazza & Castellucci, 2014), the route to celebrity might be a more obvious and easy way to extract higher rents.

Similar considerations arise from the effect of status on the relationship between performance and salary. Possessing a high status might shield professionals from performance variation because once a high status is attained, an individual’s compensation is less determined by performance. For example, this is particularly important for those who, at the end of their career, might expect a decline in their performance due to increasing age, diminished motivation, opportunistic attitude or lack of updated knowledge and, therefore, can benefit from a higher salary based on the quality of their past performance.

Besides sports, arts and show businesses, we can generalise our study results and managerial implications to several other business contexts that already have several commonalities with sports, such as visibility and worldwide exposure. In essence, our study challenges the idea that only the best performers can, in some industries, activate the virtuous circle between performance, status, celebrity and compensation, as average performers can also improve their compensation if they are able to increase their celebrity. For example, a sector recently receiving strong public interest is the food industry, particularly the role of chefs. Pushed by TV shows such as MasterChef, the job of chef has benefitted from increased attention. As a consequence, several apprentices of celebrity chefs have managed themselves to become celebrities due to their affiliations with celebrity or high-status colleagues, resulting in higher monetary compensation and better job opportunities because of their newfound celebrity, more so than objective performance.

Our results might also be generalised to CEOs of large companies in all sectors. In showing that celebrity works as a force that disconnects individual actions from the context where the actions take place, our findings are consistent with the fact that external audiences, particularly journalists, tend to trace firm performance and actions to the personalities of celebrity CEOs and not necessarily to situational factors (Hayward, Rindova, & Pollock, 2004), reinforcing the general perception that CEOs often do not face the consequences of their mistakes (Lakshman, Vo, Ladha, & Gok, 2019). Thus, the emphasis directs attention to CEOs’ celebrity more than to their results, which only magnifies their performance, which in turn impacts their compensation. This line of reasoning suggests that, in the context of their celebrity, there is a disconnection between CEOs’ performance and their actual compensation.

Limitations of the study and future research

This study has limitations that point to directions for future research. Firstly, it only considered celebrity as a positive construct. It might well be that negative celebrity stemming from illegitimate or stigmatised actions can produce opposing moderating effect on the performance–pay relationship, as organisations will retain celebrity actors who perform well despite negative perceptions. Future studies should expand the notion of celebrity from a mere measure of neutrality, as that employed here, to a measure of the content of celebrity. Secondly, in this context, actions were highly visible and clearly observed. At a minimum, we should not expect the same moderating effect to be present in those group tasks where individual results are either not easily observed or not distinguishable from the actions of others. Thirdly, professional sport is a highly idiosyncratic industry where performance is more transparent than in other industries. Despite the ease of observation, we still see the performance–pay relationship as bounded by less tangible signals, such as celebrity and status. Although it is possible to argue that these signals should play an even greater role in contexts where there is greater uncertainty and less observability of performance, the relationships we have hypothesised in such contexts are still worth examining. Fourthly, other theoretical perspectives would have been useful against which to examine our study. For example, from an agency theory perspective (Eisenhardt, 1989), it would be very interesting to study the potential opportunistic behaviours of actors at high levels of celebrity or status such as never-ending negotiations about pay level increases or special treatment, such as not being called to perform against teams at the bottom of the table. Despite these limitations, we believe that this article produced interesting evidence of the relevance of contingent factors, such as celebrity and status, in moderating the performance–pay relationship, which should be further explored in future research.

Conclusions

The objective of this study was to explore the role of intangible assets in moderating the performance–pay relationship. Building on existing studies (e.g., Della Torre et al., 2018; Montanari et al., 2008; Thrane, 2019) and a quantitative panel study of professional football players, we found support for our hypotheses that both an actor’s celebrity and high status negatively moderate the performance–pay link. We believe that our study contributes to previous studies in three ways. Firstly, we showed that the relationship between performance and pay is a function of contingent factors, which in turn modulate its strength. Indeed, a social actor’s worth – and ultimately his/her pay – might depend not only on his/her direct contribution to an organisation’s performance but also on other dimensions that are not directly related to it, such as an actor’s celebrity or status. Secondly, we contributed to the research on celebrity by showing that it might act as a substitute for performance, especially for those organisations that might need to maintain high attention. Thirdly, we contributed to the research on status by showing that it might overshadow actual performance by acting as a substitute signal for it. This study therefore represents an important extension to the understanding of the role of intangible assets in organisations and is relevant for all contexts that are exposed to high media exposure, social network attention and digital broadcasting.

Acknowledgements

The authors would like to thank the editor of M@n@gement and the anonymous reviewers for their insightful and constructive comments and suggestions, as a result of which the article has been updated to embrace the latest developments.

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Appendix 1

Appendix 1. Descriptive statistics and pairwise correlations for all variables

		Mean	S.D.	Min	Max	1	2	3	4	5	6	7	8	9	10	11	12
1	Player salary (logged)	14.638	0.89	12.429	17.273	1
2	Years of contract remaining	2.748	1.226	0	6	0.331	1
3	National team status (log-transformed)	0.142	0.16	0.008	0.693	0.156	0.018	1
4	Player status (orthog.)	0	1.001	-0.871	3.546	0.543	-0.08	-0.05	1
5	Team Champions League participation (dummy)	0	1.001	-2.251	1.553	0.424	0.206	0.135	0	1
6	Player age	28.482	3.65	20	39	-0.11	-0.56	-0	0.266	-0.16	1
7	Celebrity (orthog.)	0	1.001	-3.125	2.728	0.323	0.223	0.114	0	0	-0.28	1
8	Promotion score	5.369	6.458	0	56	0.448	0.191	0.091	0.275	0.114	-0.11	0.194	1
9	Prevention score	3.372	2.599	0.1	12.8	-0.22	-0.12	-0.01	-0.05	-0.08	0.238	-0.25	-0.49	1
10	Percentage of completed passes	79.61	6.812	53.9	94.8	0.266	0.07	0.019	0.269	0.248	-0.02	0.058	-0.2	0.19	1
11	Transfermarkt team value (prev. season, orthog.)	0	1.001	-3.06	4.226	0.219	0.084	0.068	0	0	-0.03	0	-0.06	0.001	0.229	1
12	Player performance (orthog.)	0	1.001	-2.619	5.485	0.181	0.18	0.114	0	0	-0.07	0	0.443	0.185	0.041	0	1

Footnote

^1. However, after accounting for missing data, our analyses were performed with 840 observations for 464 players.