Almighty Dollar or Root of All Evil? Testing the Effects of Money on Workplace Behavior

Abstract

Across cultures, the idea of money has dual positive and negative connotations. Consistent with this notion of duality, money-priming theory posits that the salience of money makes individuals work harder for themselves while also reducing the concern they have for others. Although research has tended to support these expectations, it has almost exclusively done so using between-persons designs in controlled lab settings. To address these limitations in the literature, we used a within-persons design in two work settings to test individual behavior change as a function of the salience of money. We did so using two samples of professional athletes and tested the extent to which priming individual pay affected both self-serving and cooperative behaviors. We operationalized the money prime in these samples as the final year of individuals’ employment contracts—a time when money is made particularly salient relative to surrounding years. Consistent with money-priming theory, within-persons analyses using a sample of basketball players from the National Basketball Association revealed that self-serving behaviors significantly increased in the final contract year relative to surrounding years. However, we did not find that cooperative behaviors decreased during the final contract year. This pattern of results was replicated using a sample of professional hockey players in the National Hockey League. These findings cumulatively suggest that although the salience of money is associated with increases in self-serving behaviors, it is not adversely associated with cooperation or team success.

Keywords

money priming compensation cooperation teams

When I was young I used to think that money was the most important thing in life; now that I am old, I know it is.

—Oscar Wilde (Proverbia, n.d., para. 2)

Nothing so evil as money ever grew to be current among men.

—Sophocles, Antigone, trans. 1900

The perception of money as both a boon (e.g., the almighty dollar) and a bane (e.g., the root of all evil) is a socially embedded dichotomy that extends across almost all cultures—money inspires hard work and actualizes charity while also breeding selfishness and enabling exorbitance (Belk & Wallendorf, 1990; Mead & Stuppy, 2014). Though it exists as an inert tool of exchange, money also carries psychological meaning beyond its instrumentality (Burgoyne & Lea, 2006; Furnham & Argyle, 1998; Lea & Webley, 2006). Recent work in the area of money priming suggests that simply thinking about money can alter an individual’s behavior in two distinct ways (Kouchaki, Smith-Crowe, Brief, & Sousa, 2013; Vohs, Mead, & Goode, 2006, 2008). On one hand, being primed with the idea of money increases self-sufficiency, or an individual’s capacity to maximize personal outcomes; specifically, it leads to greater autonomy (Vohs et al., 2006, 2008), endurance (Mogilner, 2010), and self-control (Boucher & Kofos, 2012). On the other hand, thinking about money appears to decrease concern for others; it decreases helping behaviors (Pfeffer & DeVoe, 2009; Vohs et al., 2006, 2008) and feelings of empathy (Molinsky, Grant, & Margolis, 2012) and increases unethical behaviors (Kouchaki et al.). In short, money-priming research supports the anecdotal notion that money can be both good and bad.

Because work is the primary means by which individuals obtain money (Vohs, 2010), money-priming theory has natural application to the workplace. Money-priming theory suggests that when the idea of money is salient at work—for example, at the end of an employment contract or during times when stock options may be exercised—employees are likely to behave in more self-serving ways to maximize individual outcomes while also behaving less cooperatively. However, the extent to which money alters employees’ behavior is currently unknown, as all studies to date have been conducted in controlled, laboratory settings. Thus, there is a need to better understand how this phenomenon plays out in actual employment contexts.

The need to better understand money priming as an organizational phenomenon is exacerbated by the fact that all previous research conducted in this area has used between-persons experimental designs. That is, scientists have examined differences between groups that were thinking about money (i.e., money-primed groups) and groups that were not thinking about money (i.e., control groups). Although these between-persons experiments have advanced knowledge of money priming, much less is known about how the salience of money affects behavioral changes within an individual over time. For management scholars, the examination of within-persons behavioral change is especially crucial as the extent to which any particular employee is thinking about money is likely to fluctuate greatly over time.

Consequently, the purpose of this study is to examine money’s effect on individual behavior change using a within-persons design in a field setting. On the basis of propositions from money-priming theory, we test the extent to which the salience of individual pay causes within-persons changes in both self-serving and cooperative behaviors and expect that self-serving behaviors increase and cooperative behaviors decrease during times when the idea of money is more prominent. We evaluate these hypotheses using two samples of professional athletes.

This study makes two specific contributions to the money-priming literature. First, our within-persons examination of behavior allows us to match theory with research design and more appropriately evaluate how money influences individual behavior change. Second, our use of two field samples allows us to test the core behavioral propositions of money-priming theory to enhance the ecological validity of previous findings. If money affects work behavior in the same way that it affects behavior in lab settings—particularly in terms of demonstrating reduced concern for others—then our findings would suggest that managers’ attempts to turn money into a motivator may actually have a negative impact on interdependent organizational goals.

Money-Priming Theory

The money-priming literature cumulatively suggests that thoughts of or exposure to money cause individuals to feel more self-sufficient and, thus, engage in more self-serving behavior (i.e., behaviors aimed at maximizing individual outcomes) while correspondingly reducing cooperative behaviors (i.e., behaviors that show concern for others; Kouchaki et al., 2013; Mogilner, 2010; Vohs et al., 2006, 2008). In terms of constructive self-serving behaviors, money-primed individuals tend to spend more time working (Mogilner) and put forth greater effort on difficult tasks (Vohs et al., 2006, 2008) relative to individuals exposed to neutral stimuli. At the same time, money-primed individuals also tend to behave in ways that show less concern for others relative to individuals who are not exposed to the idea of money. For example, individuals primed with the idea of money not only tend to engage more frequently in actions as benign as increasing the physical distance between themselves and others (Vohs et al., 2006, 2008) but also engage in more adverse actions, such as withholding assistance to those in need (Vohs et al., 2006, 2008) or lying to maximize individual outcomes at others’ expense (Kouchaki et al.).

The money-priming literature has advanced understanding of the cognitive mechanisms that explain the influence of money on individual behavior (e.g., Kouchaki et al., 2013; Vohs et al., 2008). Vohs et al. were some of the first to describe this mechanism by positing that thoughts of money induce a market-pricing orientation, evidenced by an inner state of self-sufficiency, which subsequently affects individual behaviors. According to Fiske (1992), a market-pricing orientation explains social behavior as a function of rational cost-benefit analyses (e.g., return on investment). When a market-pricing mode of thinking is activated, individuals view social interactions as self-serving exchange opportunities and behave in ways that are aimed at maximizing their own benefits—even if doing so demonstrates a lack of concern for others. Because money is the standard medium of market-pricing interactions (e.g., wages, commissions, taxes, rents; Fiske), Vohs and colleagues hypothesized that the idea or salience of money should elicit a market-pricing mode of thinking in individuals. Their logic was supported by their finding that subjects primed with the idea of money responded with more self-sufficiency—that is, they worked to maximize self-serving outcomes while demonstrating less concern for others (Vohs et al., 2006, 2008).

Kouchaki et al. further refined theoretical understanding by investigating the possibility that thinking about money activates a business mind-set (or decision frame) in individuals; they describe a business mind-set as a “cost-benefit analysis in which self-interest is pursued over others’ interests” (2013: 55). Kouchaki et al. built their arguments from earlier studies by Tenbrunsel and Messick (1999) and Pfeffer and DeVoe (2009), who found that a business mind-set explained individuals’ self-serving decisions to withhold cooperation in order to maximize individual outcomes. In a series of lab studies, Kouchaki et al. supported the idea that money priming is associated with increased unethical behavior (i.e., lying to maximize individual rewards) and that a business mind-set is responsible for this effect.

Taken together, these studies suggest that the idea of money induces a particular mind-set—one in which individuals are concerned chiefly with maximizing their own outcomes—that leads to the prioritization of self-interests over the interests of others. The underlying assumption is that perceptual cost-benefit analyses elicited by the salience of money lead to self-serving behaviors, which occur at the expense of cooperative behaviors. This phenomenon—though almost exclusively demonstrated in lab settings using between-persons designs—has clear implications for the workplace, particularly in interdependent settings where cooperation and collective action are paramount.

The Present Study

Our article aims to answer two questions that remain unanswered in the money-priming literature. First, does a person behave differently during times when money is a salient consideration compared to times when money is not a salient consideration? Second, can these within-persons changes in behavior be observed in work settings? Though the idea of money is arguably less subtle in a work setting relative to the typical controlled lab experiment, there are certainly times at work when the idea of money should be more prominent than others. For example, time periods preceding performance reviews, promotion decisions, or the completion of employment contracts should cause money (i.e., individual pay) to be a more focal consideration for employees. In such instances, the motivation to increase individual pay—or ensure its continuation—should be more prominent and, thus, more likely to elicit subsequent changes in behavior (Rynes, Gerhart, & Minette, 2004). Accordingly, we operationalized our workplace money prime in this study as the final year of individuals’ employment contracts. Given that employees in the final year of their contracts do not have guaranteed pay for the following year, we posit that the final contract year represents a specific period in an employee’s career when the idea of money is particularly salient. Or stated another way, the idea of money should be less salient for an employee who is guaranteed income for the following year. As a result, and consistent with money-priming theory and research, individuals in their final contract year should alter their behavior in two primary ways relative to surrounding (or noncontract) years.

First, individuals in their final contract year should engage in increased self-serving behaviors relative to other contract years. Because money should be a more prominent concern during the final contract year relative to years in which subsequent pay is guaranteed, we expect employees to adopt a business mind-set during this period, causing them to take a self-interested, cost-benefit approach to interpersonal relations (Kouchaki et al., 2013; Vohs et al., 2006). In the workplace, this mode of thinking should promote employee behaviors that are more autonomous in nature (Vohs & Baumeister, 2011)—ones that maximize individual outcomes (i.e., self-serving behaviors), regardless of whether these behaviors also contribute to group success.

Second, individuals in their final contract year should engage in fewer cooperative, group-serving behaviors relative to other contract years. Again, because of the saliency of money in the final contract year, we expect employees to adopt a transactional approach to social relations that causes them to prefer working alone and to avoid seeking help from others (Vohs, 2010). Consistent with findings that money priming weakens social bonds (Kouchaki et al., 2013) and makes individuals feel less connected to others (Mogilner & Aker, 2009; Molinsky et al., 2012), such a mind-set should manifest in the workplace as a suppression of cooperative behaviors. The propensity to devalue others as a consequence of thoughts of money is of specific importance for management scholars, given that most employees have at least some degree of work interdependence in which cooperation is integral for group success (Devine, Clayton, Philips, Dunford, & Melner, 1999; Organ, Podsakoff, & Podsakoff, 2011).

We tested our hypotheses using two samples of employed individuals embedded within interdependent teams. For both of our samples, though employees were part of a team, pay was almost wholly based on individual performance. We note that the use of individual-based pay systems in interdependent settings is prevalent (Gerhart & Fang, 2014; LeBlanc & Mulvey, 1998; Rynes, Gerhart, & Parks, 2005), making this type of setting a pertinent context for testing the behavioral propositions of money-priming theory. Such a setting is also ideal for testing our hypotheses because it creates a natural trade-off between working to maximize individual versus team outcomes (i.e., self-serving vs. cooperative behavior). A further benefit of testing our hypotheses in an interdependent team setting is that it allows us to conduct supplemental analyses to examine whether money priming has a meaningful impact on team performance. If individuals in their final contract year become more self-serving and less cooperative, then the presence of such individuals on a team should negatively affect team performance as well (Beersma, Hollenbeck, Humphrey, Moon, Conlon, & Ilgen, 2003; M. D. Johnson, Hollenbeck, Humphrey, Ilgen, Jundt, & Meyer, 2006).

Method

Setting and Sample

We first tested our hypotheses using a sample of professional basketball players in the National Basketball Association (NBA). The NBA was an ideal setting to evaluate the propositions of money-priming theory for three primary reasons. First, the end of employment contracts represents a natural time period during which money should be a focal concern that affects individual behavior. Second, the NBA’s individual-based pay structure and high task interdependence creates a behavioral trade-off between optimizing individual versus team outcomes. Finally, the objective nature of performance data tracked over time allowed us to test within-persons performance change as a function of the salience of money.

Our sample consisted of 123 NBA players who signed new employment contracts in the 2006 through 2009 summer off-seasons. The sample was restricted to those individuals who played in the three seasons¹ before and two seasons after contract signing. This range was chosen to maximize the statistical precision of within-persons analyses; it allowed for 4 years of behavioral data (2 years prior to and after the final contract year) to be compared to behavior in the final contract year for each player, resulting in a total sample of 615 performance periods for within-persons analyses. To ensure that none of the postcontract comparison years represented the final year of the new contract for a player, we restricted the sample to those players who signed contracts of at least 3 years in length. The average length of contracts signed by players in this sample was 4.28 years (SD = 0.98). The average age of the included players during the final seasons of their employment contracts was 25.85 years (SD = 3.37) with an average NBA tenure of 4.23 years (SD = 2.69). Player contract information was obtained from Hoopsworld.com (2013), and behavioral data were obtained from ESPN.com’s (2013) basketball statistics database.

Measures

We relied upon unobtrusive measures to assess the variables in this study. In contrast to typical psychological measures (e.g., questionnaires, interviews), unobtrusive measures do not require a respondent’s cooperation and, thus, allow for nonreactive variable measurement (Hill, White, & Wallace, 2013; Webb, Campbell, Schwartz, & Sechrest, 1966). Because of this, we were able to examine individual behavior change during different contract years as a naturally occurring workplace phenomenon, thereby mitigating threats to internal validity, such as testing effects or attrition (Shadish, Cook, & Campbell, 2002). Unobtrusive measures were likewise ideal for testing this study’s hypotheses because of the difficulty of assessing behavior change over time in field settings (Hill et al.).

Although distinguishing between self-serving and cooperative behaviors is challenging in work settings, given that most behaviors do not fall neatly within these two categories (De Dreu & Nauta, 2009), we drew from previous money-priming research to guide our specific operationalizations of self-serving and cooperative work behaviors. We note that our operationalizations of these behaviors are correspondent with Harder’s (1992) conceptualizations of the same behaviors in a professional basketball context. In the following section, we describe our measures and provide supplemental evidence aimed at enhancing their construct validity.

Self-serving behavior

Vohs and Baumeister (2011) described money-primed self-serving behaviors as those that are autonomous and enhance personal goal pursuit. In basketball, one behavior that is consistent with this definition is the number of points that an individual player scores through free throws and field goals (Harder, 1992). Scoring points is one of the few individual behaviors that can require little cooperation from teammates (Lewis, 2009). For example, scoring points via free throws—unimpeded shots at the basket given for a technical fault or a foul (NBA.com, 2014)—is a largely autonomous act. Field goals, or points scored while the ball is in play, can also be autonomous at times. For example, dribbling the ball up the court and shooting without first passing to a teammate is a direct and autonomous way for an individual to attempt to increase individual outcomes. Consequently, we operationalized self-serving behavior as individuals’ average points scored per game during the regular NBA season (M = 11.62, SD = 6.08).

Cooperative behavior

According to Mead and Stuppy (2014), the types of cooperative behaviors that are suppressed by thoughts of money include those that are prosocial and aimed at helping others. Thus, compared to self-serving behaviors, cooperative behaviors represent actions that require working together. In basketball, an example of cooperative behavior is an assist—an action in which an individual passes the ball to a teammate who then scores points (Harder, 1992). By definition, an assist is not an autonomous behavior as it can occur only when two team members interact. Correspondingly, according to Dictionary.com, one common definition of cooperation is “assistance” (http://dictionary.reference.com/browse/cooperation?s=t). Defense, or collective efforts to keep the opposing team from scoring, is another example of a cooperative behavior in basketball (Harder). According to Grasso (2010), defense can best be described as a team-focused variable as a result of the fact that coaches design defensive techniques for their entire team (and not individual players) and the entire team is responsible for stopping the opposing team from scoring. Accordingly, we operationalized cooperative behaviors in this sample using the separate variables of assists and defense. Specifically, we operationalized assists as the average number of assists per game during the regular season (M = 2.57, SD = 2.24). Defense was measured using a composite of average defensive rebounds, blocks, steals, and turnovers per game (M = 3.20, SD = 1.77). These factors were all weighted equally because each results in the same outcome: a change of team possession.

Supplemental validity evidence

One consequence of being primed with money is that individuals should attempt to maximize their own individual outcomes (i.e., become more self-serving). Because pay is one of the most chiefly desired individual outcomes of work—and life in general (Lea & Webley, 2006)—an additional way to substantiate our operationalizations is to show that our assessment of self-serving behavior is highly related to subsequent pay, whereas our assessments of cooperative behaviors are not. To this point, past research has revealed that the number of points scored per game is the primary predictor of player salaries in the NBA (Barnes & Morgeson, 2007; Harder, 1992) despite a number of other behaviors (e.g., assisting teammates, playing defense) that also have unique, positive effects on team performance (Simmons & Berri, 2011). We also found this to be true in our sample. Specifically, we tested points scored, rebounds, assists, blocks, and steals in the final contract season as predictors of subsequent yearly salary. In combination, these predictors explained 79% of the variance in yearly contract amount. Of the total variance explained, a relative importance analysis (J. W. Johnson & LeBreton, 2004; Tonidandel & LeBreton, 2011) revealed that points scored alone accounted for 53% of the explained variance (raw weight = .42). This was more than twice the magnitude of the next strongest source of explained variance in the tested model (rebounds = 25%, assists = 10%, blocks = 5%, steals = 7%). The fact that points scored represents the strongest single determinant of individual pay in the NBA offers support for our operationalization of points scored per game as self-serving behavior.

In order to further substantiate the validity of our measures, we followed recommendations outlined by Hill et al. (2013) and asked a sample of subject matter experts (SMEs) to rate the extent to which points scored, assists, and defense each reflect self-serving versus cooperative behaviors in the NBA. To do so, we contacted individuals with known basketball expertise (e.g., current and former basketball coaches, sports management professors) and asked them to complete a short online survey. This resulted in a sample of 26 SMEs consisting of basketball coaches, former college basketball players, and individuals employed (or formerly employed) in sports-related jobs (e.g., university athletic departments, sports marketing). More than half of our SMEs (54%) earned sports-related academic degrees (e.g., sports administration, health and physical education), and 69% reported having more than 20 years of experience with the sport of basketball.

The SMEs first rated the extent to which points scored, assists, and defense respectively represent self-serving behaviors, which were defined as “behaviors that positively impact desired individual outcomes for NBA players.” The SMEs rated behaviors using a 5-point Likert scale ranging from 1 (not self-serving at all) to 5 (extremely self-serving). For points scored, the average SME rating was 4.0 (SD = 1.08); 76% of the SMEs rated the behavior as either quite self-serving (4) or extremely self-serving (5). Conversely, the average self-serving rating for defense was 2.50 (SD = 1.04), and the average self-serving rating for assists was 2.35 (SD = 0.85). This supports the decision to operationalize self-serving behavior using points scored.

The SMEs also rated the extent to which points scored, assists, and defense represent team-serving behaviors that were defined as “behaviors that positively impact desired team outcomes in the NBA.” Correspondent with the self-serving items, these questions were answered on a 5-point scale ranging from 1 (not team-serving at all) to 5 (extremely team-serving). For points scored, the average SME rating was 3.73 (SD = 1.00), whereas the average team-serving ratings for defense and assists were 4.23 (SD = 0.86) and 4.19 (SD = 0.98), respectively. Although both defense and assists were rated, on average, as only slightly more team serving than points scored, it is important to note that self-serving and team-serving behaviors need not be mutually exclusive (De Dreu & Nauta, 2009). The key difference is that scoring points is a self-serving behavior that is likewise team serving, whereas assists and defense are team-serving behaviors that are only slightly self-serving as indicated by SMEs. In summary, the SMEs rated points scored as the most self-serving and the least team serving of the possible behaviors, whereas they rated defense and assists as the most team serving and the least self-serving.

To build upon the preceding results, we also asked the SMEs to indicate which behaviors are most and least likely to increase the dollar amount of NBA players’ employment contracts. For the behavior judged most likely to increase pay, 96% of the SMEs selected points scored (one selected defense). For the behavior judged least likely to increase pay, 62% selected assists, 38% selected defense, and 0% selected points scored. Consequently, because defense and assists are team-serving behaviors that were judged by SMEs to be much less strongly linked to individual outcomes, we assert that they best represent cooperative behaviors based on our conceptual definition, whereas scoring points best represents a self-serving behavior, given its dominant connection with individual pay. In combination with previous research that has conceptualized these variables similarly (e.g., Harder, 1992), these supplemental findings support the validity of our operationalizations of both self-serving and cooperative behaviors in the present context.

Contract year

The final year (or season) of employment contracts for NBA players represents a period during which money should be particularly primed relative to other years. This is because the NBA is a clear pay-for-performance setting in which individual pay is unambiguously linked to individual performance (Barnes & Morgeson, 2007; Barnes, Reb, & Ang, 2012) and also because performance at the end of employment contracts has a strong association with subsequent contract amounts in the NBA (Barnes et al.). In addition, because NBA players have limited windows of time to earn money as professional athletes—few play professionally for more than 10 years—the individuals in this sample should have been particularly motivated by money during the final year of their employment contracts. Taken together, this suggests that the final contract year represents a time when the thought and pursuit of money is more strongly activated relative to preceding or subsequent years.

Because the focus of our analyses was to compare players’ behavior in the final contract year to surrounding years, irrespective of whether those years occurred before or after the final contract year, we created a dichotomous variable such that years were coded as the final contract year (1) or a comparison year (0). This variable was entered as a within-persons (Level 1) predictor of individual behavior in our statistical models.

Control variables

At the within-persons level (Level 1), we controlled for the average number of minutes played per game each season (minutes played) to ensure that we captured true within-persons performance change independent of variance in the opportunity to perform (M = 27.02, SD = 8.48). Controlling for minutes played was particularly important because, on average, players tended to play more minutes per game during the final contract year (M = 28.95, SD = 7.34) relative to other years (M = 26.54, SD = 8.87). This could spuriously suggest that performance increased when it was only the opportunity to perform that increased. We note that although average minutes played increased during final contract years, these two variables were only weakly correlated (r = .11), suggesting that multicollinearity was not a concern for our two independent variables.

Although minutes played was the only control variable we included in our final models, there were a number of other within-persons (Level 1) and between-persons (Level 2) covariates that we included initially. At the within-persons level, we controlled for the number of games played per season—a proxy for player injury—and whether players changed teams from one season to the next. We also controlled initially for the between-persons factors of player age, NBA tenure, team tenure, and player position because of their expected impacts on player performance.² However, because none of these variables affected the interpretation of our results, we excluded them for parsimony (Atinc, Simmering, & Kroll, 2012; Becker, 2005).

Analyses

We used multilevel modeling to test our hypotheses. Multilevel modeling was necessary because of the nesting of individual performance episodes (i.e., seasons) within players for the within-persons analyses and the nesting of teams within franchises for our supplemental team-level analyses (Kreft & De Leeuw, 1998). Because the focus of each of our hypotheses was on the influence of Level 1 predictors, we used group-mean centering for our statistical models (see Enders & Tofighi, 2007; Hofmann & Gavin, 1998). All analyses were conducted using Mplus Version 7 (Muthén & Muthén, 2012).

Results

Preliminary Multilevel Tests

Before testing our hypotheses, we determined whether it was most appropriate to estimate fixed versus random effects in our multilevel models (Aguinis, Gottfredson, & Culpepper, 2013; Peugh, 2010). We elected to follow this procedure rather than estimating random effects as a default because including unnecessary random effects in multilevel models reduces statistical power and can lead to parameter estimation errors (Peugh; Raudenbush & Bryk, 2002; Singer & Willett, 2003).

Although we expected that mean within-persons performance (i.e., intercepts) would vary across players as a result of readily observed between-persons performance differences, it was unclear whether within-persons relationships between contract year and performance (i.e., slopes) would vary across players. Thus, to test for slope variance, we first estimated random intercept and fixed slope (RIFS) models, which estimated variance in intercepts but not slopes across players. Second, we tested random intercept and random slope (RIRS) models, which estimated variance in both intercepts and slopes across players. We then compared the two models’ –2 log likelihood ratios for each dependent variable using the likelihood ratio test outlined by Peugh (2010) to determine whether one model was better fitting than the other (with a significant difference indicating meaningful slope variance). Likelihood ratio tests revealed that there were no statistically significant differences between the RIFS and RIRS models for points, χ²(2) = 0.52, n.s., assists, χ²(2) = 2.97, n.s., or defense, χ²(2) = 0.33, n.s., indicating that the more parsimonious fixed slope models fit the data just as well as the random slope models. This suggests that for each model, a single regression coefficient (i.e., slope) adequately represented the relationship between contract year and individual behavior (whether self-serving or cooperative) across players (Aguinis et al., 2013; Peugh). That is, there was no meaningful between-persons slope variance. Consequently, we estimated the slopes between contract year and each of our dependent variables as fixed effects in our statistical models.

Because we included minutes played as a within-persons covariate in our models, it was necessary to follow this same procedure to test whether the relationships between minutes played and our dependent variables varied across players. Likelihood ratio tests showed that there were statistically significant differences between the RIFS and RIRS models for points scored, χ²(2) = 175.27, p < .05, assists, χ²(2) = 264.71, p < .05, and defense, χ²(2) = 143.78, p < .05. These results indicate meaningful slope variance in the relationships between minutes played and our dependent variables. Consequently, we estimated the slopes between minutes played and each dependent variable as random effects in our statistical models.

Hypothesis Tests

Descriptive statistics and intercorrelations for this study’s within-persons variables are reported in Table 1. Our hypotheses were, first, that self-serving behaviors increase when money is more salient and, second, that cooperative behaviors decrease when money is more salient. Results for within-persons tests of these hypotheses are reported in Table 2. With regard to the first hypothesis, results revealed that players scored statistically significantly more points per game in their final contract year (γ = 0.38, p < .01) relative to both preceding and subsequent years after controlling for average minutes played per season. This supports the proposition from money-priming theory that individuals engage in more self-serving behaviors when money is made salient.

Table 1

Within-Persons Descriptive Statistics and Variable Intercorrelations

Variable	1	2	3	4	5	M	SD
1. Points scored	—					11.62	6.08
2. Assists	.52**	—				2.57	2.24
3. Defense	.35**	−.09*	—			3.20	1.77
4. Contract year	.11**	.05	.07	—		0.20	0.40
5. Minutes played	.88**	.61**	.49**	.11**	—	27.02	8.48

Note: N = 615. Contract year is dummy coded 1 for the final contract season and 0 for all other seasons.

p < .05, two-tailed.

p < .01, two-tailed.

Table 2

National Basketball Association Results for Contract Year Predicting Individual Behavior

Variable	Points scored	Assists	Defense
Fixed effects
Intercept (γ₀₀)	11.62 (0.48)**	2.57 (0.18)**	3.20 (0.17)**
Contract year (γ₁₀)	0.38 (0.12)**	−0.04 (0.05)	0.11 (0.06)
Minutes played (γ₂₀)	0.58 (0.03)**	0.13 (0.01)**	0.13 (0.01)**
Variance components
Within-persons residual variance (σ²)	2.08	0.22	0.32
Intercept variance (τ₀₀)	28.00	4.13	3.40
Slope (γ₂₀) variance (τ₁₁)	0.06	0.01	0.01
Intercept-slope covariance (τ₀₁)	1.28	0.21	0.15
Pseudo R²	.78	.66	.59

Note: N = 615 performance episodes (i.e., seasons) nested within 123 individuals. All estimates are unstandardized; values in parentheses are standard errors. The slopes including contract year as an independent variable were fixed, whereas the slopes including minutes played as an independent variable were random. Contract year is dummy coded 1 for the final contract year and 0 for all other years. Pseudo R² = the percentage of within-persons variance explained by the models’ fixed effects.

p < .01.

Although there is sufficient evidence to consider points scored as a valid indicator of self-serving behavior, an additional indicator of self-serving behavior could simply be the extent to which a player possessed the ball when they were on the court (i.e., “ball hogging”). A player who possesses the ball more has a greater likelihood of maximizing their individual outcomes when money is primed. Consequently, we also assessed self-serving behavior using John Hollinger’s “usage rate” statistic—“the number of possessions a player uses per 40 minutes” (ESPN.com, 2014)—and then retested our first hypothesis with usage rate as the dependent variable³ (M = 18.54, SD = 4.59). Because usage rate already accounts for minutes played, we did not include minutes played as a control variable. Consistent with our initial hypothesis test, this secondary analysis revealed a statistically significant increase in player usage rates (γ = 0.36, p < .05) during the final contract year relative to surrounding years. That is, money-primed individuals tended to “hog the ball” more than non-money-primed individuals. This offers additional support for the notion that employees become more self-serving during times when money is primed.⁴

We proposed in our second hypothesis that cooperative behaviors would decrease when money is salient. We tested this by examining both assists per game and defensive performance as dependent variables. These analyses revealed that there were no substantive changes in either type of behavior (assists: γ = −0.04, n.s.; defense: γ = 0.11, n.s.) in the final contract year relative to the 4 surrounding contract years. Combined with the preceding analysis, these results suggest that although players tended to increase their self-serving behaviors in their final contract years, there was no corresponding decrease in cooperative behaviors.

Supplemental Team-Level Analysis

As a follow-up analysis in the NBA sample, we examined whether the presence of team members for whom money was more salient (i.e., players in the final year of their contracts) had a meaningful impact on team performance. Because interdependent team settings often require team members to defer personal interests in order to maximize team outcomes, increased self-serving behaviors by team members were expected to be negatively associated with team performance (Beersma et al., 2003; M. D. Johnson et al., 2006). We tested this expectation at the team level of analysis using a sample of 120 teams nested within 30 franchises from the 2005–2006 through the 2008–2009 NBA seasons. We defined a team as the set of players within a franchise for a given season.

We operationalized team performance as the percentage of wins in a season (i.e., the number of games won divided by the number of games played). This is the key metric used to gauge team success throughout professional sports. However, as a more fine-grained analysis, we also tested the dependent variables of team offensive efficiency and defensive efficiency—the number of points a team scores and allows per 100 possessions, respectively (ESPN.com, 2013)—as well as the ratio of assisted to unassisted points scored by the team (M = 14.94, SD = 1.08). This latter metric (assist ratio) represents the percentage of a team’s possessions that end in an assist (ESPN.com) and signifies the extent to which teammates assisted each other in scoring versus creating scoring opportunities more independently.

The core team-level variable entered to predict team performance was the presence of team members in their final contract year. This was operationalized as the number of starters on a given team who were in their final contract years and ranged from a minimum of zero to a maximum of four players per team (M = 0.80, SD = 0.85). We restricted this analysis to starters—operationalized as the five team members who played the most games in a given season—because starters have the greatest opportunity to affect team performance. We controlled for midseason trades of starters (M = 0.43, SD = 0.68) in this analysis because personnel changes (i.e., turnover) tend to be disruptive for team performance (Heavey, Holwerda, & Hausknecht, 2013) and could thus affect the interpretation of results.

Before conducting our supplemental test, we again determined whether it was most appropriate to test fixed or random slopes in our statistical model using likelihood ratio tests. These tests revealed no meaningful variance in the relationships between the number of money-primed team members and team win percentage, χ²(2) = 5.45, n.s., or between the examined control variable (i.e., midseason trades) and team win percentage, χ²(2) = 1.79, n.s. Thus, we estimated both relationships using fixed regression coefficients in our model.

As reported in Table 3, results indicated that the presence of players in their final contract year had no effect on team win percentage (γ = 0.01, n.s.) when controlling for midseason trades. To determine whether perhaps other meaningful team performance metrics were affected, we also tested team offensive and defensive efficiency and team assist ratio as dependent variables. However, consistent with the preceding analysis, results showed that the number of players in their final contract years had no meaningful effects on offensive efficiency (γ = 0.85, n.s.), defensive efficiency (γ = 0.72, n.s.), or assist ratio (γ = −0.10, n.s.). These results remained nonsignificant even after midseason trades was removed from the statistical models as a covariate. Cumulatively, these results suggest that the presence of players in their final contract year has no appreciable effect on meaningful team outcomes.

Table 3

Team-Level Results for Individuals in Their Contract Year Predicting Team Performance

Variable	Win percentage	Offensive efficiency	Defensive efficiency	Assist ratio
Fixed effects
Intercept	0.50 (0.02)**	93.97 (1.21)**	94.01 (1.08)**	14.94 (0.18)**
Contract players	0.01 (0.01)	0.85 (0.95)	0.72 (1.12)	−0.10 (0.08)
Trades	−0.04 (0.02)**	0.74 (1.25)	2.53 (1.14)*	−0.08 (0.18)
Variance components
Within-teams residual variance (σ²)	0.01	54.01	51.86	0.54
Intercept variance (τ₀₀)	0.01	0.12	0.11	0.62
Pseudo R²	.07	.01	.04	.01

Note: N = 120 teams nested within 30 franchises. All estimates are unstandardized; values in parentheses are standard errors. The slopes involving contract players and trades as independent variables are fixed. Pseudo R² = the percentage of team-level variance explained by the models’ fixed effects.

p < .05.

p < .01.

Replication Sample

Because our within-persons results were only partially supportive of money-priming theory, we obtained an additional sample to test the robustness of these findings. Specifically, we obtained a sample of professional hockey players from the National Hockey League (NHL) to replicate our within-persons findings regarding both self-serving and cooperative behavior. As with the NBA sample, the NHL sample was ideal for testing our research questions because (a) the conclusion of employment contracts in the NHL creates a real-world money prime during which individuals should be more likely to alter their behaviors to maximize future pay, (b) professional hockey is an interdependent team context in which individuals are primarily paid on the basis of individual performance, and (c) individual performance data are objectively measured and tracked over time.

Although the NHL and the NBA are similar in a number of respects (e.g., they are both professional sports leagues), there are some noteworthy distinctions between the two samples that allow us to extend the generalizability of our findings. For example, whereas the majority of NBA players (approximately 80%) are from the United States (Helin, 2013), the vast majority of NHL players (76%) are from countries outside of the United States. Additionally, 76% of NBA players are African American, whereas over 90% of NHL players are Caucasian (Lapchick, Hippert, Rivera, & Robinson, 2013; Vogl, 2013).

Method

The NHL sample consisted of 166 offensive players⁵ (i.e., forwards) who signed employment contracts in the NHL between the 2006 and 2011 summer off-seasons. We restricted the sample to individuals who had at least four but ideally five consecutive seasons of performance and for whom only one of those consecutive seasons constituted the final year of an employment contract. This resulted in a within-persons sample of 768 performance episodes (i.e., seasons of performance). The average age of players during their final contract year was 27.31 years (SD = 4.31) with an average NHL tenure of 5.90 years (SD = 3.86). Player contract information was obtained from Capgeek.com (2014), whereas player performance data were obtained from Hockey-reference.com (2014).

Similar to the NBA sample, we operationalized self-serving behavior as individual goals scored in a season (M = 19.40, SD = 10.78) and cooperative behavior as assists made in a season (M = 27.86, SD = 16.13). We likewise created a dichotomous variable for contract year that differentiated between the final contract season (1) and other contract seasons (0) for each player. Also like the NBA sample, we controlled for the opportunity to perform in the NHL sample by entering average time on ice (M = 17.10 min, SD = 3.57) as a within-persons covariate.

Results

We first estimated preliminary RIFS and RIRS multilevel models to determine whether there was meaningful variance in slopes across players. Likelihood ratio tests revealed no statistically significant differences between the nested models for the relationships between contract year and either goals scored, χ²(2) = 2.43, n.s., or assists, χ²(2) = 0.26, n.s., indicating that slopes did not vary meaningfully across players. We thus estimated these relationships using fixed slopes. However, because the relationships between time on ice (i.e., minutes played) and goals scored, χ²(2) = 11.97, p < .05, and assists, χ²(2) = 11.89, p < .05, varied meaningfully across players, we estimated random slopes for these relationships in our statistical models.

Hypothesis test results in the NHL sample are reported in Table 4. Consistent with our previous findings, results revealed a statistically significant increase in goals scored for players during their final contract year (γ = 2.20, p < .01) relative to previous and subsequent years. Despite this increase in self-serving performance, however, there was no corresponding decrease in assists during the final year of employment contracts (γ = 1.09, n.s.). This pattern of effects directly mirrors our findings in the NBA sample. Taken together, the findings across these two samples offer robust evidence to suggest that although the final year of employment contracts is associated with increases in self-serving behaviors, it is not associated with a corresponding decrease in cooperative behaviors. We discuss the implication of these findings next.

Table 4

National Hockey League Results for Contract Year Predicting Individual Behavior

Variable	Goals scored	Assists
Fixed effects
Intercept (γ₀₀)	19.06 (0.66)**	27.36 (1.06)**
Contract year (γ₁₀)	2.20 (0.57)**	1.09 (0.77)
Time on ice (γ₂₀)	1.97 (0.18)**	2.54 (0.26)**
Variance components
Within-persons residual variance (σ²)	34.76	67.18
Intercept variance (τ₀₀)	65.11	27.36
Slope (γ₂₀) variance (τ₁₁)	0.83	1.03
Intercept-slope covariance (τ₀₁)	4.37	10.87
Pseudo R²	.29	.22

Note: N = 768 performance episodes (i.e., seasons) nested within 166 individuals. All estimates are unstandardized; values in parentheses are standard errors. The slopes including contract year as an independent variable were fixed, whereas the slopes for time on ice as an independent variable were random. Contract year is dummy coded 1 for the final contract year and 0 for all other years. Pseudo R² = the percentage of within-persons variance explained by the models’ fixed effects.

p < .01.

Discussion

Money carries with it the cultural connotation of being both good and bad (Belk & Wallendorf, 1990; Mead & Stuppy, 2014). In line with this expectation, money-priming theory and existing lab research suggest that money has both favorable and unfavorable effects on individual behavior, such that the salience of money increases self-serving behaviors that maximize individual outcomes while decreasing cooperative behaviors (Kouchaki et al., 2013; Vohs et al., 2006, 2008). We tested these theoretical expectations in two work settings using a within-persons design. In doing so, we revealed partial support for money’s dual effects on individual behavior at work. First, we confirmed that individuals’ self-serving behaviors increased during times when money was more salient (i.e., final contract years) relative to times when money was less salient (i.e., other contract years). However, we did not find support for the proposition that cooperative behaviors decrease as a function of the salience of money—nor did we find that money priming had any adverse effects on team performance.

Theoretical Implications

This study contributes to the management literature by extending money-priming theory to the workplace and testing relevant hypotheses in two different employment settings. Perhaps most significantly, our findings move beyond between-persons examinations to show, using a within-persons design, how individual employees change their behavior when the idea of money is made more salient. Consistent with theory, our finding that employees increased self-serving behaviors only during the final contract year (i.e., when money is most salient) supports the idea that money activates a business mind-set wherein self-serving concerns dominate. Specifically, money-primed employees were more likely to engage in behaviors that were more insular and autonomous (e.g., scoring points in games) and that were most strongly connected to desired individual outcomes (i.e., pay). Thus, one takeaway from this research is that activating the construct of money seems to cause employees to want more of it and pursue it more strongly. This particular finding suggests that integrating money-priming theory with the compensation and goal-setting literatures may be fruitful considering that these areas have repeatedly found money to be a strong motivator of individual behavior (Gupta & Shaw, 2014; Locke, Feren, McCaleb, Shaw, & Denny, 1980; Rynes et al., 2004).

Contrary to our hypothesis, money priming did not have an impact on cooperative behaviors. However, we hesitate to say that this indicates a lack of support for money-priming theory. As a result of the nascent state of the literature, there are still a number of unknown factors that may explain the effects of money on individual behavior (Mead & Stuppy, 2014). For example, although research suggests that the money-induced activation of a business mind-set weakens social bonds (Kouchaki et al., 2013), it is possible that the weakening of social bonds comes primarily in the form of indifference. Developing an indifference to coworkers may be different from refusing to help or cooperate with them and leaves open the possibility that thinking about money may not necessarily reduce cooperative behaviors in a work setting. One explanation for this may come from consideration of social norms.

Because this was the first money-priming study to investigate individuals nested within interdependent teams, it is possible that the existence of workplace social norms played a role in our findings. When work is highly interdependent, norms for cooperation are likely to exist (De Dreu, 2007)—as are sanctions for violating those norms (Kerr, 1995). Thus, any rational cost-benefit analysis (induced by the idea of money) should incorporate the possibility of sanctions as part of the utility calculus. Consistent with this point, findings by Tenbrunsel and Messick (1999) showed that the detrimental influence of a business mind-set on group cooperation (i.e., making decisions for the benefit of the collective) was weakened by the likelihood of incurring sanctions for acting against the collective good (to maximize individual outcomes). This result should presumably apply to any situation with a high likelihood of sanctions for failing to act for the benefit of others. In the case of the present study, individuals were likely aware that failing to play good defense (a cooperative behavior) may have led to reprimands from coaches and fellow teammates, ultimately resulting in reduced playing time and fewer opportunities to score points to maximize individual outcomes.

In summary, although money is theorized to elicit a business mind-set that supersedes concern for others (e.g., Kouchaki et al., 2013; Vohs et al., 2006, 2008), the presence of norms for cooperation may have prevented the individuals in our samples from decreasing their cooperation levels during times when money was made salient. This is presumably because money-induced cost-benefit analyses calculated that violating norms would not have been the most efficient means of maximizing individual outcomes because of the possibility of sanctions. Future research is needed to directly test the existence of social norms for cooperation as a moderator of money’s impact on cooperative behavior.

Practical Implications

Practically speaking, this study provides evidence that the salience of money does alter individual behavior. Specifically, when money is a prominent concern, individuals appear to increase their efforts to behave in ways that are most likely to maximize future pay. This is theorized to be a function of a business mind-set elicited by the salience of money. Thus, during times when money is a more prominent consideration (e.g., before performance reviews, at the end of employment contracts), performance specifically tied to individual pay is likely to improve. However, it is noteworthy that this improvement appears to be only temporary such that performance drops to more normal or typical levels during times when concerns for money are less prominent (e.g., after signing a new contract or receiving a promotion). As such, managers would be well suited to consider more than just recent performance when making administrative decisions. This is consistent with practical recommendations regarding the consideration of typical versus maximum performance in organizational decisions (Beus & Whitman, 2012; Sackett, Zedeck, & Fogli, 1988). Whereas performance during times when money is salient may be more reflective of maximum performance levels—when motivation is constrained to be high—performance during times when money is less salient may be more indicative of typical performance that is a function of more normal and sustainable motivation levels (Sackett, 2007; Sackett et al.). Because of this, managers should seek to differentiate employee performance during times when money is a prominent concern (e.g., prior to administrative decisions) from performance under more normal conditions to gain a more accurate sense of how employees are likely to perform in the future.

Although the idea of money as a motivator of work behavior has been maligned, particularly for its presumed negative effects on cooperation in interdependent settings (e.g., Deming, 1986; Kohn, 1993; Pfeffer, 1998), it is noteworthy that we observed no changes in cooperative behavior associated with the salience of money. Rather, the only observed changes in individuals’ behavior in this study’s samples were adaptive (at least from an individual perspective). Thus, we failed to support the notion that money is a detrimental influence on individual behavior in teams. Consistent with results obtained by Locke et al. (1980), who compiled evidence indicating that people tend to work harder when motivated by money, our results suggest that practices that increase the salience of money for individuals will have a similar impact.

Limitations and Future Directions

As this was the first study to extend money-priming theory to work settings, there are limitations worth noting. First, the generalizability of our samples is limited. For example, higher-than-average compensation levels, limited career durations, and heightened public scrutiny distinguish professional athletes from employees in other work domains. However, despite the uniqueness of these samples, we contend that they represent informative contexts for examining compensation-related research questions (see Barnes et al., 2012; Day, Gordon, & Fink, 2012; Ertug & Castelucci, 2013; Harder, 1992; Trevor, Reilly, & Gerhart, 2012). Although lab studies have done much to advance understanding of issues related to money and compensation, researchers have cautioned that the paucity of studies investigating research questions in real-world contexts limits the generalizability of compensation-related findings (Rynes et al., 2005). In this vein, a particular benefit of professional sports contexts is that we were able to test our research questions under simplified, highly controlled conditions (Day et al.; Wolfe et al., 2005) as well as use samples of real employees working for real pay on real teams.

A further study limitation is that we were unable to test the presence of a business mind-set as the mediating mechanism by which the salience of money affects individual behavior change. Rather, our samples limited us to the use of unobtrusive behavioral measures to evaluate money-priming theory’s behavioral propositions. As a result, we could only infer that the salience of money induced a business mind-set on the basis of previous empirical results (i.e., Kouchaki et al., 2013; Pfeffer & DeVoe, 2009; Tenbrunsel & Messick, 1999). However, in line with behavioral consistency theories that suggest that behaviors are indicative of underlying psychological constructs (Hill et al., 2013), we assert that our finding that self-serving behaviors significantly increased when money was made salient during the final contract year is consistent with the theoretical expectation regarding the presence of a business mind-set.

A related limitation is that we were unable to directly assess whether it was money that was primed during the final contract year relative to surrounding years. Thus, it is possible that something other than the salience of money motivated the observed behavior change in the two examined samples. However, it is unclear to us what a plausible alternative explanation might be. Rather, we assert that the combination of theory, past empirical results, and the current findings offer a strong triangulation of evidence to support our expectation that the final year of employment contracts represents a meaningful workplace money prime.

The preceding limitations highlight the need for future studies to extend and substantiate our findings. In particular, we believe that the management literature would benefit from additional money-priming studies that address three main considerations. First, a constructive extension of this research should utilize an employee sample from a divergent work setting (i.e., nonsports) to enhance the generalizability of our findings. Second, future money-priming studies should maintain a within-persons design to most appropriately test the within-persons propositions of money-priming theory. Although many jobs where employment contracts are renewed could satisfy these considerations, occupations that mirror NBA and NHL samples in terms of contract length and time frame would be particularly amenable. For example, university professors and corporate lawyers tend to have contracts that expire around the 6-year mark when decisions are made regarding tenure or achieving partner status (i.e., lifelong employment). In these cases, self-serving and cooperative behaviors could be examined in the years before and after the final contract year using a methodology very similar to ours.

In addition, we recommend that future research directly assess the existence of a business mind-set as a mediating mechanism in the effect of money on behavior. As demonstrated by Kouchaki et al. (2013), a business mind-set can be measured both via psychological scales and by less obtrusive means (e.g., word completion tasks). Specific instances in which a business mind-set should transmit the effects of money on workplace behavior are likely to be observed with managers when renewing group-level employment contracts (e.g., construction projects, research grants, outsourced services). Such time periods should enhance the salience of money for leaders, leading to mind-sets that ultimately affect leaders’ enacted priorities and decisions. For example, the salience of money for a construction manager nearing a project deadline could result in a stronger business mind-set that changes the balance of priorities from quality and safety to speed and production (Wallace & Chen, 2006; Zohar, 2011). Another possibility would be to assess the mind-set and subsequent actions of CEOs surrounding time periods when their company stock prices are likely to be particularly salient, such as immediately preceding quarterly earnings announcements. Examinations such as this are needed to extend our findings and substantiate a business mind-set as the mechanism by which the salience of money affects workplace behavior.

Conclusion

Is the influence of money on individual work behavior both good and bad? Although previous work in the area of money priming suggests that the answer to this question is yes (Kouchaki et al., 2013; Vohs et al., 2006, 2008), our findings suggest that the salience of money appears to be only a net positive for individuals. Whereas self-serving behaviors increased during the final year of employment contracts when money was a prominent individual concern, there were no corresponding decreases in cooperative behaviors in the final contract year relative to surrounding years. There were likewise no adverse team-level effects associated with the presence of team members in the final year of their contracts. As the first within-persons evaluation of money-priming theory in a field setting, this study enhances understanding of the practical impact of money on workplace behavior. We encourage future research to expand upon these findings to better understand the psychological influence of money at work.

Footnotes

Acknowledgements

This article was accepted under the editorship of Deborah E. Rupp. We wish to thank Ed Locke, Chris Barnes, Tim Chandler, and Suzy Caleo for their helpful comments on earlier drafts of this article.

Notes

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