The Effect of Individual Levels of Self-Monitoring on Loyalty to Professional Football Teams. (Self-Monitoring on Loyalty)
Mahony, Daniel F., Madrigal, Robert, Howard, Dennis, International Journal of Sports Marketing & Sponsorship
* Keywords: Team Loyalty, Self-monitoring, Fan Behavior, Professional Football
Although building and maintaining a loyal fan base has become critical for sport organizations, little research has been done in this area. An extensive investigation of loyalty exists within the consumer behavior literature, but the current study was one of the first to examine loyalty within a team sport context.
In order to better understand differences in individual loyalty to athletic teams, the purpose of the current study was to examine the impact of the personality variable, self-monitoring. A number of studies in the social psychology literature found the construct of self-monitoring influenced the amount of loyalty exhibited by individuals in a variety of settings (Jenkins, 1993; Richards, 1994; Snyder, Gangestad, & Simpson, 1983; Snyder & Simpson, 1984). In each study, high self-monitors were less loyal than low self-monitors. A similar relationship between self-monitoring and team loyalty would have definite implications for sport marketers. If high self-monitoring fans are less loyal and, therefore, more likely to switch favorite teams, sport marketers would be well advised to focus their marketeering efforts on appealing to high self-monitors, particularly when the tendency for disloyalty is high (e.g. team is performing poorly, popular players are traded).
Consistent with prior loyalty research, the study examined loyalty behavioral and attitudinal dimensions. The behavioral dimension was operationalized using length of allegiance (number of years as a fan) and frequency of team switching (number of times team allegiance was switched). The attitudinal dimension was operationalized using Mahony, Madrigal, & Howard's (1998) Psychological Commitment to Team (PCT) scale. The respondents (n = 151) were college students at a large Southwestern university in the United States. The relationship between loyalty and self-monitoring, operationalized by Snyder & Gangestad's (1986) 18-item Self-Monitoring Scale, was examined using hierarchical regression and chi-square analyses.
The study provided support for the hypothesis that low self-monitors will display greater behavioral loyalty than high self-monitors, but did not provide support for a similar hypothesized relation between self-monitoring and attitudinal loyalty. The study, therefore, provided some support for the hypothesis that team support will be affected by team performance more for high self-monitors than low self-monitors. This finding is the first to demonstrate that at least one personality characteristic impacts team loyalty.
This finding also has implications for sport marketers. Because the current study suggests high self-monitors are more likely to switch favorite teams, sport marketers should focus their efforts on preventing this type of disloyal behavior. While the study provides evidence that high self-monitors are more prone to defect or switch their allegiance from favored teams, sports marketers can implement programs to reduce the potential for this behavior to occur among high self-monitors.
Three specific preventative actions are discussed in the paper, including: a) stressing the positive impact that being a fan of the team will have on the individual's public image, b) attempting to elicit emotional reactions from team advertisements, and c) carefully choosing endorsers to be used in commercials. While further research on advertisements in sport is warranted, the findings in the current study provide some guidance to sport marketers.
Understanding fans has become critical to sport organizations in recent years. As a result of increased competition and rising financial pressures (e.g. Fulks, 1996; Howard, 1999), sport organizations can not afford fluctuations in fan support and need to maintain a large base of loyal fans. Loyal fans can be quite valuable to an organization because they are more likely to attend games, purchase team merchandise, watch games on television, and listen to games on the radio. All of these activities can lead to increased profitability for the team through increased revenue. For example, the University of Notre Dame (USA) has been able to use its national following and large number of highly loyal fans to assure sellouts of all of its home football games, to consistently be one of the leaders among American Universities in merchandise sales, and to sign the most lucrative television contract in American college football (Eitzen & Sage, 1997).
Although sport executives in the past seemed to take such high levels of fan loyalty and support for granted, the negative reaction following the 1994 baseball strike suggests otherwise. Baseball teams reported drops in attendance as high as 49% in the beginning of the 1995 season (Antonen, 1995) and television ratings for baseball on TBS dropped about 23% after the 1994 strike (Mihoces, 1995). Yet, some teams appeared to be able to avoid a negative impact from the strike. There was considerable variance among teams in regard to fan reaction and some teams were able to maintain the same levels of attendance and a few even reported a gain (Antonen, 1995).
Just as there are differences among teams with regards to the level of loyalty among their fans, there appear to be individual differences between fans with regards to their team loyalty. While some fans remain loyal to the same team their entire lives, others seem to switch whenever the situation related to their favorite team is negative (e.g. team performs poorly).
The question is: why are some fans consistently very loyal, while others seem to demonstrate such little loyalty to their favorite teams? Moreover, what can sport marketers do to prevent fans with a tendency to be disloyal from leaving them? Also, what can they do to steal disloyal fans away from other teams? The focus of the current study was to examine research related to sport fans and research in social psychology to try to determine why there are differences among individuals and in particular to identify fans likely to be disloyal. Further, the current study then attempted to present research based suggestions for maintaining loyalty among these generally disloyal fans.
Sport Fan Research
In spite of its obvious importance, little is known about fans' loyalty to their favorite teams (Zillman & Paulus, 1993). Still, there has been some important research on sport fans. Hirt, Zillman, Erickson, & Kennedy (1992) reported that highly identified fans indicated that their mood, self-esteem, estimates of future personal performance, and estimates of future team performance were all positively impacted when the team won and were negatively impacted when the team lost. This research would seem to indicate the relationship between the team and the individual can be quite strong in the mind of the fan, so that success or failure by the team becomes equated with success or failure by the fan.
Because of the potential for both positive and negative impacts, it would seem logical that some fans will adjust their relationship with the team in different situations. In fact, Cialdini, Borden, Thorne, Walker, Freeman, and Sloan (1976) found individuals increase their association, or Bask in Reflected Glory (BIRG), with sport teams when the teams performed well. Specifically, Cialdini et al. found that students were more likely to wear university-related clothing and use the inclusive pronoun "we" following a winning effort by the football team.
A corollary of the BIRGing phenomenon is the tendency to Cut Off Reflected Failure (CORF; Snyder, Lassegard, & Ford, 1986). Snyder et al. found that respondents tended to distance themselves from groups that performed poorly. Evidence of this effect was also present in Cialdini et al. 's study when students used the exclusive pronoun "they" when describing a loss by their university's football team.
It appears, therefore, that associating with a sports team serves a tactical function in regard to self-presentation. Based on the relationship between self-presentation and association with sport teams, the authors of the current study identified the personality variable of self-monitoring as an individual difference variable with potential to explain differences in team loyalty. A relationship between self-monitoring and team loyalty would be particularly useful because of the considerable amount of research on self-monitoring in general (e.g. Snyder & Gangestad, 1986) and on reactions to advertisements among high and low self-monitors (e.g. DeBono & Packer, 1991).
Self-monitoring "is concerned with individual differences in the willingness or ability to modify behavior in accordance with the norms of situational appropriateness" (Miller & Thayer, 1988, p. 545). Snyder (1974) suggested that high self-monitors are more sensitive to their self-image while in social situations and are more likely to adjust their behavior to enhance this image. In contrast, the behavior of low self-monitors is dictated by their internal attitudes, dispositions, and traits. Low self-monitors do not possess the desire, social skills, or perceptual sensitivity to adjust their behavior in accordance with situational demands (Miller & Thayer, 1988). As such, self-monitoring represents an individual difference variable that should have an interesting effect in a sport setting. High self-monitors should be more interested in using an association with a team to benefit their self-presentation. Low self-monitors, on the other hand, would be expected to maintain a consistent level of loyalty even whe n the team performs poorly.
A number of studies have supported the theory that high self-monitors are more concerned with their public image. Snyder, Berscheid, and Glick (1985) found that high self-monitors were more likely to choose an attractive date with an undesirable personality than an unattractive date with a desirable personality. The choice made by high self-monitors appears to be based on the belief that others would view them more positively if they were seen with an attractive date.
Research has found that high self-monitors are very concerned with how a certain product or service will affect their image (DeBono & Packer, 1991; DeBono & Snyder, 1989; Graeff, 1996; Lennon, Davis, & Fairhurst, 1988; Snyder & DeBono, 1985). For example, high self-monitors rated advertisements for clothing more highly if the ads focused on how wearing the clothing would affect the consumer's image as opposed to those that focused on the high quality of the clothing (Lennon et al., 1988). They were even willing to spend more money for the product because of the anticipated benefits to their public image (Lennon et al., 1988).
Because of their desire to maximize their public image, high self-monitors "often display marked situation to situation shifts in the image they convey to other people" (Snyder & DeBono, 1985, p. 588). Moreover, the willingness of high self-monitors to allow situational factors, which are more variable than internal attitudes, to determine their behavior has led some researchers to hypothesize that high self monitors would have lower levels of commitment and less longevity in their relationships (Jenkins, 1993; Richards, 1994; Snyder, Gangestad, & Simpson, 1983; Snyder & Simpson, 1984).
This proposed link between self-monitoring and loyalty has been well established in the literature. For example, research has shown that low self-monitors are more loyal to their best friends (Snyder et al., 1986), dating partners (Snyder & Simpson, 1984), employers (Jenkins, 1993), and religious affiliations (Richards, 1994). Whereas the commitment of high self-monitors appears to be greatly influenced by situational factors, low self-monitors tend to be more committed to a wide array of attitude objects, including people and groups.
Before examining its relationship with self-monitoring, it is also important to briefly discuss the concept of loyalty. The topic of team loyalty has just recently begun to be investigated (Murrell & Dietz, 1992; Wakefield, 1995). Wakefield and Sloan (1995) have defined team loyalty as "an allegiance or devotion to a particular team that is based on the spectator's interest in the team that has developed over a period of time" (p. 159). They found that loyal fans are less affected by team performance and situational constraints (stadium quality, etc). A spectator's loyalty toward a team may be thought of as a type of brand loyalty in that the two share certain characteristics. Olson and Jacoby's (1971) widely cited six-point definition describes brand loyalty as a (1) biased (2) behavioral response (3) expressed over a period of time (4) by some decision making unit (5) with respect to one or more alternative brands (6) as a function of psychological processes.
From this definition, brand loyalty researchers have generally agreed that loyalty is comprised of both behavioral and attitudinal dimensions (e.g. Day, 1969; Dick & Basu, 1994; Jacoby & Chestnut, 1978). Interestingly, the two dimensions are not always positively correlated. For example, Backman and Crompton (1991) found that some individuals are high in behavioral loyalty, but low in attitudinal loyalty. Termed spuriously loyal, such individuals may be behaviorally loyal simply due to habit or a lack of alternatives. The low attitudinal commitment shown by these individuals suggests they are more likely to switch allegiance when a more attractive option becomes available.
Accordingly, the need to consider both behavioral and attitudinal loyalty appears critical in understanding the loyalty construct. Behavioral loyalty simply refers to one's repeated use of a particular brand. In contrast, attitudinal loyalty represents the psychological commitment one has to a brand. Psychological commitment, in this case, refers to "the tendency to resist change in preference in response to conflicting information or experience" (Crosby & Taylor, 1983, p. 414). A number of recent studies have emphasized the importance of resistance to change when assessing attitude strength (Haugtvedt & Petty, 1992; Haugtvedt & Wegener, 1994). Based on the research related to brand loyalty, the authors have defined team loyalty as a person's willingness, based on psychological commitment to a team, to behave in a manner that demonstrates support for that team over a period of time.
The purpose of this study was to answer the following question: to what extent can self-monitoring be used to predict differences in an individual's loyalty to their favorite athletic team? Team loyalty was assessed using both behavioral and attitudinal measures. Based on the literature, it was hypothesized that low self-monitoring individuals would be more loyal than high self-monitors. Because a great deal is known about self-monitoring's influence on behavior and information processing, information related to self-monitoring would be helpful in finding strategies to maintain and increase the loyalty levels of current fans, as well as means for attracting new fans.
In order to more accurately assess the relationship between self-monitoring and team loyalty, two covariates were considered in three of the four hypotheses.
Gender was one covariate used for two reasons. First, Gantz and Wenner (1991) presented findings suggesting women and men differ in their behavior as sport fans. For example, they found men have greater interest in television sports and spend more time watching television sports, whereas women often watch sports because it is something to do with friends/family. Second, studies have found men are more likely than women to be high self-monitors (Friedman & Miller-Herringer, 1991; Nesler, Tedeschi, & Storr, 1995; Stewart & Carley, 1984). Although the same relationship between self-monitoring and team loyalty was expected for both men and women, these prior studies suggested that using gender as a covariate in the current study was advisable. Level of interest in professional football was also used as a covariate because it was believed that an individual's enthusiasm toward the sport might be related to some of the dependent variables, including number of years as a fan of favorite team and psychological commit ment to the favorite team.
Specifically, the following hypotheses were tested. After controlling for gender and level of interest in professional football:
* Hypothesis 1: self-monitoring will be negatively related to the number of years as a fan of the current favorite team.
* Hypothesis 2: self-monitoring will be positively related to the number of teams a fan has identified as being, or having been, his/her favorite.
* Hypothesis 3: self-monitoring will be negatively related to psychological commitment to the current favorite team.
Finally, data was collected both before and at the end of the season. During both phases of data collection, respondents were asked to identify their favorite team. Using these responses, a fourth hypothesis was tested to further examine the tendency among high and low self-monitors to switch favorite teams. Based on the prior research, the following prediction was made.
* Hypothesis 4: during the professional football season examined, more high self-monitors than low self-monitors will report having switched their favorite team.
When designing the current study, one of the major decisions concerned the specific sport and the level of competition to examine. A professional sport was chosen rather than a college sport because the extremely high involvement that students have with college teams could bias the results (Zillman, Bryant, & Sapolsky, 1989).
American football was selected because of its popularity in the United States and the general awareness of teams participating in the National Football League (NFL). American football was found to be the most popular of the four major professional team sports in the United States according to a USA Today /Gallup Poll conducted at the time of data collection (as cited in Mihoces, 1995).
The original respondent pool (N=176) was recruited from two undergraduate classes at the University of Oklahoma. Of the original sample, 153 respondents also completed the second phase of the study. However, two of the surveys were not usable. Therefore, the final sample size for the current study was 151.
The use of homogeneous respondents was preferred in this study given the goal was theory application and not effects application (Calder, Phillips, & Tybout, 1981). Therefore, while the statistics from the current study (e.g. number of favorite teams, score on the self-monitoring scale) are not generalizable beyond this sample, any relationship between self-monitoring and loyalty is generalizable to a wider population.
All respondents were asked to complete Snyder and Gangestad's (1986) Self-Monitoring Scale (using a 5-point Likert scale). Respondents were then asked to record their gender and age and answer a series of questions related to (a) the respondent's level of interest in professional football (measured using a 8-point Likert scale), (b) the length of time the respondent had been a supporter of his or her favorite team, and (c) the number of favorite teams the fan had during his or her life. The questionnaire took approximately 10 minutes to complete.
A second phase of data collection was conducted in a manner similar to phase one. Mahony, Madrigal, & Howard's (1998) Psychological Commitment to Team scale (PCT) was administered to respondents during the 14th week of the season (NOTE: At the time of the study, the NFL season was 16 weeks long with each team playing one game per week). Respondents were also asked at the top of the PCT to indicate which team was their favorite at that point in the season.
The instructions given to participants prior to phase one indicated they would be completing surveys for a number of unrelated studies. The intent was to prevent respondents from discovering the purpose of the study and prevent them from trying to answer in a socially desirable manner. Because the PCT scale included questions that asked whether the respondent would change their team allegiance in a variety of situations, it was the most obvious team loyalty measure. Unfortunately, there was no way to prevent the subjects from deducing this was a measure of team loyalty.
The current study used Snyder and Gangestad's (1986) 18-item Self-Monitoring Scale (SMS) with a Likert-type format to measure self-monitoring (see Appendix A for scale items). Snyder's (1974) original scale had 25items, but the scale had greater internal consistency after Snyder and Gangestad eliminated seven items. The Likert-type format was chosen because it allows for a more thorough analysis (Cohen & Cohen, 1975) and was found by Miller and Thayer (1989) to have greater internal consistency (.75) than the scale using the true/false format advocated by Snyder and Gangestad. However, a median split was done on self-monitoring scores in order to examine the fourth hypothesis. All respondents with total scores of 54 or greater were labeled as high self-monitors.
During the first phase of the study, respondents were asked to indicate their gender, which was then coded as 0 for females and +1 for males.
Level of Interest in Professional Football.
Level of interest in professional football was measured with a one-item measure on a eight-point scale that asked "How strongly do you see yourself as a fan of professional football (Not at All a Fan/Very Much a Fan)?". A one-item measure was used because no multi-item measure currently existed for assessing interest in professional football and this measure was considered sufficient for the purposes of the current study.
Number of Years as a Fan of Favorite Team. During phase one of the current study, the number of years a respondent was a fan of their favorite professional football team was measured using a single item: "How many years have you been a fan of that (their favorite) team?".
Number of Favorite Professional Football Teams
The number of favorite professional football teams was measured through the use of the following questions during phase one: (a) "Which NFL team is currently your favorite?" and (b) "Which NFL team was your favorite when you first began watching professional football?." If the team in (a) was the same as the team in (b), the number of favorite teams was equal to 1. For example, if Respondent 1 said that their favorite team was currently the Dallas Cowboys and their favorite team when they first began watching professional football was the Dallas Cowboys, their number of favorite teams was equal to 1 after the first two questions. In contrast, if Respondent 2 indicated that they were currently a fan of the Dallas Cowboys, but had been a fan of the New York Giants when they began watching professional football, their number of favorite teams was equal to 2 after the first two questions.
A final item asked the subjects to "List any other NFL teams that were your favorite team at some point in your life (if there were no other teams write "None")". The number of teams listed here, assuming there were any, was added to the number of favorite teams from (a) and (b). For example, if Respondent 1 indicated that there were no other teams that had been his/her favorite, then the number of favorite teams was equal to 1 (1+0). If Respondent 2 indicated that the Chicago Bears and the Cleveland Browns had both once been their favorite team, the number of favorite teams was equal to 4 (2+2).
A simpler measure, such as asking respondents how often they had switched their team allegiance, was not used because it was thought that respondents would be more likely to guess the question was intended to assess behavioral loyalty and they might answer in a socially acceptable manner. This would have been especially problematic with high self-monitors who are more concerned with how they present themselves and would most likely try to present themselves as very loyal.
In addition to assessing past behavioral loyalty toward the favorite team, a second approach to measuring behavioral loyalty was built into the data collection. Fans were asked to indicate "Which NFL team is currently your favorite?" during both phase one (before the season) and phase two (near the end of the season) of data collection. For those respondents who indicated that they had the same favorite team before the season and at the end of the season, SWITCH was equal to 0. When respondents identified a different team at the end of the season than they did at the beginning of the season, SWITCH was equal to 1.
Psychological Commitment to Team
Mahony et al.'s (1998) Psychological Commitment to Team (PCT) scale (see Appendix B for scale items) was used to assess attitudinal loyalty. The development of the PCT scale relied heavily on the work of Pritchard, Havitz, and Howard (in press), who developed an instrument to measure psychological commitment in service marketing contexts, and on Churchill's (1979) model for scale development. After converting some of the items used in the Pritchard et al. scale, additional items were generated by Mahony et al. Based on Crosby & Taylor's (1983) definition of psychological commitment (i.e. "the tendency to resist change") and the recent emphasis on the importance of measuring resistance to change when assessing attitude strength (Haugtvedt & Petty, 1992: Haugtvedt & Wegener, 1994), a heavy emphasis was placed on capturing resistance to change when generating the items for the PCT scale. Scale properties were then assessed using four samples in three different team sport contexts. The 14-item scale (using a seve n-point Likert-type format) that emerged from this analysis exhibited acceptable levels of internal consistency (.88 or higher) and strong evidence of construct and predictive validity (Mahony et al., 1998).
Before analyzing the four hypotheses, descriptive statistics were computed. Means and standard deviations were computed for the self-monitoring scale (SMS), level of interest in professional football, years as a fan of favorite team, number of favorite teams, and psychological commitment to team (PCT) scale for men, women, and the overall sample. Coefficient alphas were then computed for the SMS and the PCT scale. A correlation matrix was also computed for the SMS, level of interest in professional football, years as a fan of favorite team, number of favorite teams, and the PCT scale.
A series of hierarchical regressions were used to analyze the Hypotheses 1, 2, and 3. In each analysis, the covariates were entered first (gender and level of interest in professional football), followed by self-monitoring. This was done to determine if self-monitoring was related to the team loyalty measure after controlling for gender and level of interest in professional football. The dependent variables in the three regression equations were years as a fan of the favorite team (Hypothesis 1), the number of favorite teams (Hypothesis 2), and psychological commitment to the favorite team (Hypothesis 3).
The results of each analysis, including the overall R, the overall [R.sup.2], the adj [R.sup.2], [DELTA][R.sup.2] at each step, Beta weights, F values, and significance levels, were presented and interpreted. In particular, the interpretation of the results focused on the [DELTA][R.sup.2], which indicates the amount of additional variance in the dependent variable explained by the independent variable. For example, if the [DELTA][R.sup.2] for self-monitoring was equal to .10 in Hypothesis 1, it would mean that 10% of the variance in the number of years as a fan of the favorite team would be explained by the individual's level of self-monitoring. In addition, significance levels will be closely examined. When evaluating the significance levels for each hypothesis, p < .05 was considered to be significant and p < .10 was considered to be marginally significant.
Finally, a chi-square analysis was used to examine Hypothesis 4. A median split was used to dichotomize self-monitoring. All respondents scoring 54 or greater were classified as high self-monitors. The other variable was whether or not the fan had switched their favorite team during the season (SWITCH). The results of the analysis, including [chi square] and significance levels, were presented and interpreted.
The final sample (N=151) included 89 men and 62 women with a mean age of approximately 23 years 6 months. The overall means and standard deviations for each of the variables are presented, as is a breakdown by sex, in Table 1. Coefficient alphas for the Self-Monitoring Scale and the Psychological Commitment to Team scale were .71 and .88, respectively. Both values are above the minimum standard of .70 suggested by Nunnally and Bernstein (1994). A correlation matrix for self-monitoring, number of favorite teams, number of years as a fan of favorite team, psychological commitment to team, and level of interest in professional football is presented in Table 2.
The first hypothesis suggested low self-monitors would indicate they have been fans of their favorite team for a longer period of time than would high self-monitors. A hierarchical regression analysis, shown in Table 3, was performed to determine whether self-monitoring made a contribution above and beyond gender and interest in professional football in predicting the number of years an individual has been a fan of their favorite NFL team. The overall regression using all three variables was significant, F(3, 147) = 17.46, p <. 001. The results indicated gender made a significant contribution to the prediction of the number of years as a fan of the favorite team, [DELTA][R.sup.2] = .217, p < .001. Men indicated they had been fans of their favorite team for a longer period of time than women. The results also indicated level of interest in professional football made a significant contribution to the prediction of the number of years as a fan of the favorite team, [DELTA][R.sup.2] = .026, p < .025, after the co ntribution by gender. Respondents with a greater interest in professional football indicated they had been fans of their favorite team for a longer period of time than those who were less interested in professional football.
Finally, the results showed self-monitoring explained a marginally significant (p < .10) amount of the variance in number of years as a fan of favorite team, [DELTA][R.sup.2] = .019, p < .054, after controlling for gender and level of interest in professional football. The relationship between self-monitoring and the number of years as a fan of the favorite team was negative. Therefore, the results of the hierarchical regression analysis provided moderate support for Hypothesis 1. Although the support for the hypothesis was only moderate, low self-monitors did report having been a fan of their current favorite team for a longer period of time than high self-monitors and, therefore, demonstrated greater loyalty to their favorite team with regards to the duration aspect of team loyalty.
The second hypothesis predicted high self-monitors would have switched their favorite team more often and would therefore identify more teams as having been their favorite. The results of the hierarchical regression, with the number of teams an individual identifies as currently, or as having once been, their favorite NFL team as the dependent variable, are shown in Table 4. The overall regression using all three variables was significant, F(3, 147) = 7.18, p < .001. The results indicated gender did not make a significant contribution to the prediction of the number of favorite teams, [DELTA][R.sup.2] = .003, p < .479. In contrast, level of interest in professional football did make a significant contribution to the prediction of the number of favorite teams, [DELTA][R.sup.2] = .034, p < .023, after controlling for gender. Respondents who indicated they had greater interest in professional football also indicated they had had more favorite teams than respondents who had less interest in professional football.
Finally, the hierarchical regression indicated self-monitoring explained a significant amount of the variance in number of favorite teams, [[DELTA]R.sup.2] = .090, p < .001, after accounting for the variance due to gender and level of interest in professional football. Consistent with the prediction in Hypothesis 2, the relationship between self-monitoring and the number of favorite teams was positive. Low self-monitors identified fewer teams as having once been their favorite than did high self-monitors. In other words, low self-monitors were less likely to report having switched their favorite team and therefore demonstrated greater behavioral loyalty to their favorite team.
The third hypothesis suggested low self-monitors would indicate greater psychological commitment to their favorite team. The results of the hierarchical regression, with psychological commitment to their favorite NFL team (PCT) as the dependent variable, are shown in Table 5. The overall regression using all three variables was significant, F(3, 147) = 15.54, p < .001. The results indicated gender made a significant contribution to the prediction of PCT, [[DELTA]R.sup.2] = .108, p < .001. Men indicated they were more psychologically committed to being a fan of their favorite team than were women. The results also showed that, after controlling for gender, level of interest in professional football made a significant contribution to the prediction of PCT, [[DELTA]R.sup.2] .125, p <.001. Increased levels of interest in professional football were related to greater psychological commitment to their favorite team. Finally, the hierarchical regression analysis indicated self-monitoring did not explain a significan t amount of the variance in PCT, [[DELTA]R.sup.2] = .008, p < .223, after significant contributions were made both by gender and level of interest in professional football. Therefore, the results of the analysis did not support Hypothesis 3.
The final hypothesis predicted high self-monitors would change their favorite team more often than low self-monitors during the season. Of the 151 respondents in the study, 18 indicated they had switched their favorite team during the 1994 NFL season. The results of the chi-square analysis indicated there was a significant relationship between self-monitoring and switching, [chi square] (df=1) = 7.42, p < .006. Analysis of the frequencies indicated 14 of the 18 respondents who switched their favorite team during the 1994 season were high self-monitors. Thus, the results of the chi-square analysis provided support for Hypothesis 4. High self-monitors were more likely to switch favorite teams (and therefore demonstrated less loyalty) than low self-monitors. This finding is consistent with the results for Hypothesis 2, which found high self-monitors had switched their favorite team more often during their life. The authors believe, given the highly homogeneous character of the sample, that finding such a high pr oportion of switchers to be high self-monitors (78%) lends credence to the hypothesis despite the small size of the sample.
Self-Monitoring as a Predictor of Behavioral Loyalty
Summary of Results
The present study demonstrated the efficacy of self-monitoring as a predictor of behavioral loyalty. Self-monitoring was able to predict a moderately significant amount of the variance in the number of years a respondent had been a fan of their current favorite NFL team. As predicted in Hypothesis 1, low self-monitors reported having been a fan of their current favorite team for a longer period of time than high self-monitors. The finding that low self-monitors demonstrate extended behavioral loyalty is consistent with the results reported by Snyder and Simpson (1984), who found that low self-monitors exhibited greater levels of commitment to their dating partners for longer periods of time than did high self-monitors. However, it should be noted that the results were only moderately significant and self-monitoring only predicted 1.9% of the variance in number of years as a fan of the favorite team. Therefore, one should not place too much emphasis on this result alone.
Next, the study examined the extent to which a strictly behavioral measure of loyalty would be influenced by self-monitoring. Because switching team allegiance appears to be one of the most disloyal actions possible for sports fans, whether a participant has switched their team allegiance may be one of the best measures of an individual's loyalty to their favorite athletic teams. Both statistical analyses used in the current study found a significant relationship between self-monitoring and the switching of team allegiance. As predicted in Hypothesis 2 and 4 respectively, low self-monitors reported they had fewer favorite teams (meaning that they switched their favorite team fewer times) and were less likely to report having switched their favorite team during the current season. It should be noted that the participants in the study were relatively young and the average number of favorite teams was only 2.05. It is possible that an older sample would have greater variance in the number of favorite teams becau se they would have had more time to switch.
The tendency of low self-monitors to demonstrate greater team loyalty is consistent with behavior patterns inclined toward more stable, long term associations. Snyder and Simpson (1984) found low self-monitors less inclined to switch dating partners and, more recently, Jenkins (1993) found that low self-monitors were significantly less inclined than high self-monitors to change jobs. The current study is the first to offer evidence that there is at least one personality characteristic that "predisposes spectators to form particularly strong affiliations" with athletic teams (Zillman & Paulus, 1993, p.604).
Implications for Sport Marketers
One implication of these findings is that low self-monitors are more loyal to their favorite athletic teams and will be less influenced by situations generally leading to disloyal behavior (e.g. poor team performance). Low self-monitors tend to be loyal to their favorite teams for longer and are less likely to switch favorite teams even if the team does poorly. Because of their strong loyalty and consistent support for their favorite teams, low self-monitoring fans are quite valuable to a sport team. Sport marketing efforts focusing on young viewers should try to attract low self-monitors, who can be a valuable long-term resource if they are reached as the enter the market. However, marketing efforts focusing on current low self-monitoring fans would seem to be less worthwhile. Those who are currently fans of the marketer's team are unlikely to abandon this team regardless of the situation and trying to steal away low self-monitoring fans from other teams would be very difficult and probably not cost effectiv e.
In contrast, sports marketers would do well to concentrate their efforts on appealing to high self-monitors when the situation for the team is not good with regards to the potential for disloyalty (e.g. poor team performance, low levels of team popularity, loss of a popular player). High self-monitors are more likely to become disloyal when the benefits of being a fan are decreased and marketers should focus their efforts on maintaining the allegiance of high self-monitoring fans. In addition, a sport organization attempting to attract defectors from other teams, might concentrate their efforts on appealing to high self-monitors. Particularly when the situation is positive for the team, efforts to attract these defectors may be quite successful and cost effective.
Suggestions for Sport Marketers
The first suggestion for sport marketers seeking to maintain the loyalty of current fans or to attract fans of other teams would be to emphasize that being a fan of their team will have a positive impact on the fan's image and that current fans are benefiting socially from their association with the team. Prior research has found that high self-monitors tend to react more favorably to advertisements that emphasize image as opposed to product quality (DeBono & Packer, 1991; DeBono & Snyder, 1989; Lennon et al., 1988; Snyder & DeBono, 1985). High self-monitors rated advertisements for products more favorably (Lennon et al., 1988; Snyder & DeBono, 1985), were willing to spend more money for the products (Lennon et al., 1988; Snyder & DeBono, 1985), were more willing to try a new product (Snyder & DeBono, 1985), rated the quality of the products higher (DeBono & Packer, 1991; DeBono & Snyder, 1989), rated the advertisements as more self-relevant (DeBono & Packer, 1991), and had better recall of the advertisements (DeBono & Packer, 1991) when the advertisement emphasized the positive impact that the product would have on the user's image. The image suggested by the brand is particularly important to high self-monitors when the product or service is publicly consumed (Graeff, 1996). Because sporting events are often publicly consumed, the potential impact of the team's image on the high self-monitor's image would be expected to be strong.
One example of this focus on image over quality was used a few years ago by the San Francisco Giants, a Major League Baseball team in the United States. The Giants used an advertising campaign that suggested only a "tough" fan could survive a game at Candlestick Park (due to the sometimes harsh weather conditions in the stadium). This "tough" image would probably be appealing to many high self-monitors. The attempt by marketers for the Giants to turn a negative quality of the product and turn it into a positive impact on image is a good model for other sport marketers to follow. In addition, advertisements which feature well-known and well-liked celebrities who remain loyal to the team despite its record may also be successful. Campaigns such as these, which focus more on the fan (and less on the quality of the product) and, at the same time, emphasize the positive self-presentation benefits of being a fan (e.g. will be viewed as tough, loyal, popular), could be very successful with high self-monitors and may work well when the team is performing poorly.
Another suggestion for sport marketers would be to try and elicit an emotional reaction from the high self-monitoring fans when trying to get them to attend or watch team games or to prevent them from switching their team allegiance. Prior researchers has found that the behavioral intentions of high self-monitors, as opposed to low self-monitors, were more likely to be related to emotional reactions (Darley & Lim, 1992). One way to accomplish this may be to use old sport footage of emotional moments in the team's history to elicit such a reaction.
In addition, sport marketers may also want to use an attractive source (i.e. endorser) to deliver the message when they are presenting strong arguments. DeBono and Hamish (1988) found high self-monitors were more likely to systematically process a message presented by. an attractive source and heuristically process a message from an expert source. An attractive source who may be especially effective with high self-monitors would be someone who has the image that the high self-monitors are seeking to attain (such as the celebrity previously described). However, it should be noted that much of the prior research on high self-monitors' reactions to advertisements dealt exclusively with products (e.g. cars, clothes, beverages). Therefore, additional research is needed to determine which type of advertisements would be most successful in impacting the behavior of high self-monitors in the unique service industry of sport.
Self-Monitoring as a Predictor of Attitudinal Loyalty
Summary of Results
The present study failed to show the usefulness of self-monitoring as a predictor of attitudinal loyalty. In the literature review, it was noted that the definition of brand loyalty included an attitudinal dimension (Jacoby & Chestnut, 1978). Self-monitoring, however, did not contribute significantly to the prediction of psychological commitment to team after accounting for gender and level of interest in professional football. Moreover, it is interesting to note that the correlation and the beta coefficients were in the opposite direction from the prediction made in Hypothesis 3 (see Table 2 and Table 5). The psychological commitment to the favorite team actually had a positive correlation with self-monitoring.
There are a few plausible explanations for this unexpected finding. First, high self-monitors indicated that they were greater fans of professional football than low self-monitors. Although not predicted a priori, this finding is not surprising given the popularity of professional football in the United States. As stated earlier, a USA Today /Gallup Poll indicated that American football was the most popular of the four major professional team sports in the United States and its greatest popularity was among fans in the 18-29 age group (as cited in Mihoces, 1995). Because almost all the participants in the current study were in this age group, it is reasonable to hypothesize that high self-monitors would be more likely to indicate interest in professional football than low self-monitors because football is popular among their peers. In addition, one of the major needs satisfied by being a sports fan is social approval (Zyto-Sitkiewcz, 1991) and high self-monitors may actually be greater sports fans in general than low self-monitors because they have a greater need for social approval.
Second, the Psychological Commitment to Team scale was the only measure of loyalty in the current study for which the participants could surmise the construct being measured. The measures of behavioral loyalty were asked in ways that made it difficult for the participants to guess the true purpose of the study. However, the Psychological Commitment to Team scale was by its very nature an obvious measure of loyalty. Because most people would prefer to be labeled a loyal or "diehard" fan as opposed to a disloyal or "fair-weather" fan, it is possible that high self-monitors attempted to answer in a socially appropriate manner by indicating that they would remain loyal to their favorite team even when the team was performing poorly, a popular player was traded, etc.
Third, a number of researchers have reported that although high self-monitors may indicate attitudes towards certain types of behavior that are equal to or stronger than the attitudes expressed by low self-monitors, they demonstrate less attitude-behavior consistency (Kraus, 1995; Paulus, 1982; Snyder & Tanke, 1976; Zanna, Olson & Fazio, 1980). In particular, Ajzen, Timko, & White (1982) indicated high self-monitors are less likely to follow through on their intentions. For example, a high self-monitor who strongly disagrees with the statement "I might rethink my allegiance to my favorite NFL team if this team consistently performs poorly," may still switch their team allegiance when confronted with a situation in which the team has had a disappointing season. Finally, it is possible that all three of these factors combined to lead to these results. Regardless of the reasons, self-monitoring was a not a significant contributor to the prediction of psychological commitment to team in the hierarchical regressio n and the reason for this result is not clear at this time.
Implications for Sport Marketing Researchers
Moreover, three implications emerge from this finding. First, using only an attitudinal measure of team loyalty would be a mistake for sport marketing researchers. High self-monitors may indicate they are psychologically committed to their favorite team, but their behavior clearly indicates that they do not behave in a more loyal manner. Past behavior should be combined with current levels of psychological commitment to best predict future behavior (Bagozzi, 1992). Second, future researchers may have to use more creative methods to attempt to capture the attitudinal dimension of loyalty for high self-monitors. Because it is possible that respondents guessed what the Psychological Commitment to Team scale was measuring, more discrete methods may be needed to assess this dimension for high self-monitors.
Finally, sports marketers would still be best advised concentrate their efforts on maintaining the allegiance of high self-monitors during periods of poor team performance or declining team popularity. Overall, the results indicate that high self-monitors are harder to attract and/or retain during lean times. At the same time, it is likely that low self-monitors will generally be less influenced by team performance factors and will continue to attend in spite of a decline in their teams' fortunes. Given the greater tendency of high self-monitors to defect when a team is suffering through a disappointing season, sport marketers should emphasize the positive impact that being a fan of the team will have on the high self-monitor's image, try to elicit an emotional response through advertisements, and use endorsers who are attractive to high self-monitors along with strong arguments.
It is interesting to note that in the current study, high self-monitors demonstrated slightly higher levels of attitudinal loyalty, but lower levels of behavioral loyalty, while low self-monitors were higher in behavioral loyalty and lower in attitudinal loyalty. This finding may indicate that there are alternative explanations for why individuals are spuriously or latently loyal. Traditionally, spuriously loyal customers (high in behavioral loyalty and low in attitudinal loyalty) were believed to be the customers who purchase the product or service because of habit and were not very resistant to change (Backman & Crompton, 1991). However, in the current study low self-monitors would be labeled as spuriously loyal, but they tend to be very resistant to change.
In contrast, latently loyal customers (low in behavioral loyalty and high in attitudinal loyalty) have generally been described as being psychologically committed (resistant to change) consumers who are prevented from acting on their strong attitude because of some barrier (e.g. limited product availability, lack of time, lack of money) (Backman, 1991). Based on their responses in the current study, high self-monitors would be labeled as latently loyal, but some of their disloyal behaviors (switching favorite teams) are not a result of any of the barriers identified and are simply a result of their general tendency toward disloyal behavior. Therefore, the findings in the current study may change some of the explanations for why some consumers are categorized as spuriously or latently loyal. Instead of the traditional explanations for these groups, some of the individuals may be in these groups because of a personality difference. Low self-monitors may need to have only a low level of psychological commitment in order to be resistant to change (and, therefore, their loyalty level may be mislabeled as spurious), while high self-monitors may not be very resistant to change even at high levels of psychological commitment. Although this contention needs further examination, it would certainly impact our current view of loyalty.
A number of other implications for further research emerge from the current study. First, a future study should attempt to use a true experiment to examine the relationship between self-monitoring and an individual's loyalty to their favorite athletic team. Such a study could manipulate team performance and team popularity within hypothetical scenarios to determine the extent to which loyalty intentions are moderated by self-monitoring. Specifically, the study would test the hypothesis that the loyalty intentions of high self-monitors would be influenced more by the manipulations than will the loyalty intentions of low self-monitors. The current examination only used studies in a naturalistic setting and greater control should be sought in some future studies.
Second, future research should again examine the relationship between attitudinal loyalty and self-monitoring. The failure to achieve significance -- and the fact that the correlation is in the opposite direction from what was expected -- is intriguing and warrants further examination. Third, future studies should examine other behavioral measures of loyalty, such as watching televised games, attending games, and wearing team merchandise, to determine if the relationship between behavioral loyalty and self-monitoring is consistent across behaviors.
Finally, future studies could examine how high self-monitors and low self-monitors react to different types of advertisements. Researchers have already shown that individuals react differently to advertisements based on their self-monitoring tendencies (Darley & Lim, 1992; DeBono & Harnish, 1988; DeBono & Packer, 1991; DeBono & Snyder, 1989; Lennon, et al., 1988; Snyder and DeBono, 1985), but none has examined advertisements for sport teams. This research would be of particular interest to sport marketers.
Beyond the implications emerging directly from the current study, there are other areas of research which could be beneficial to our understanding of sport consumers. First, future research is needed to determine how and why associations with athletic teams emerge and how they become stronger or weaker over time. Second, future studies should examine the relationship between fans and their favorite players. It is possible that they relationship may be stronger than the relationship to the favorite team and may lead to more modeling of behavior on the part of the fan. For example, the relationship between Michael Jordan and his fans is often more important to the fans than their relationship with the Chicago Bulls (Yardley, 1998) and it would be interesting to examine the role that the relationship plays in the life of the Jordan fans.
Third, future studies should attempt to explore more psychological variables that may be helpful in explaining the behavior of sport consumers. Information related to this impact could be especially important when developing marketing campaigns and be helpful in explaining the success and failure of prior campaigns. Finally, more research is needed to understand the impact of relationships with sport teams and sport figures on the sales of non-sports related products and services. A number of corporations sponsor sport teams and sport events, advertise during games, and use athlete endorsers in hopes of increasing sales. However, our limited understanding of sport fans makes it more difficult to predict the impact of these efforts and makes it nearly impossible to understand why these efforts succeed or fail. Overall, more research is needed on sport fans in order to have a better theoretical understanding of the complexities of their behavior.
1. I find it hard to imitate the behavior of other people.
2. At parties and social gatherings, I do not attempt to do or say things that others will like.
3. I can only argue for ideas which I already believe.
4. I can make impromptu speeches on topics about which I have almost no information.
5. I guess I put on a show to impress or entertain others.
6. I would probably make a good actor.
7. In a group of people I am rarely the center of attention.
8. In different situations and with different people, I often act like very different persons.
9. I am not particularly good at making other people like me.
10. I'm not always the person I appear to be.
11. I would not change my opinions (or the way I do things) in order to please someone or win their favor.
12. I have considered being an entertainer.
13. I have never been good at games like charades or improvisational acting.
14. I have trouble changing my behavior to suit different people and different situations.
15. At a party I let others keep the jokes and stories going.
16. I feel a bit awkward in public and do not show up quite as well as I should.
17. I can look anyone in the eye and tell a lie with a straight face (if for a right end).
18. I may deceive people by being friendly when I really dislike them.
Psychological Commitment to Team (PCT) Scale
1. I might rethink my allegiance to my favorite NFL team if this team consistently performs poorly.
2. I would watch a game featuring my favorite National Football League (NFL) team regardless of which team they are playing.
3. I would rethink my allegiance to my favorite NFL team if management traded away its best players.
4. Being a fan of my favorite NFL team is important to me.
5. Nothing could change my allegiance to my favorite NFL team.
6. I am a committed fan of my favorite NFL team.
7. It would not affect my loyalty to my favorite NFL team if management hired a head coach that I disliked very much.
8. I could easily be persuaded to change my NFL team preference.
9. I have been a fan of my favorite team since I began watching professional football.
10. I could never switch my loyalty from my favorite NFL team even if my close friends were fans of another team.
11. It would be unlikely for me to change my allegiance from my current favorite NFL team to another.
12. It would be difficult to change my beliefs about my favorite NFL team.
13. You can tell a lot about a person by their willingness to stick with a team that is not performing well.
14. My commitment to my favorite NFL team would decrease if they were performing poorly and there appeared little chance their performance would change.
Table 1 Means and Standard Deviations for Variables in Hypothesis 1 as a Function of Gender (N=151) Gender Variable Male Female Overall (n = 89) (n = 62) Self-Monitoring (scores range from 18 to 90) M 54.84 53.11 54.13 SD 9.37 8.10 8.99 Number of Favorite Teams M 1.99 2.15 2.05 SD 1.32 1.35 1.33 Number of Years as a Fan M 12.31 6.18 9.79 SD 5.65 5.93 6.50 Psychological Commitment (scores range from 14 to 98) M 74.27 64.16 70.12 SD 15.01 13.07 15.05 Interest in Pro Football (scores range from 1 to 8) M 6.46 4.77 5.77 SD 1.65 1.89 1.93 Table 2 Correlations Among Variables in Hypothesis 1 for the Overall Sample (N = 151) Football Fan Measures SM NUMFAV YEARFAV PCT FFL SM 1.00 .31 *** -.07 .15 + .13 + NUMFAV 1.00 -.28 *** -.07 .14 + YEARFAV 1.00 .43 *** .35 *** PCT 1.00 .47 *** FFL 1.00 Note: SM = Self-Monitoring NUMFAV = Number of Favorite Teams YEARFAV = Number of Years as a Fan Favorite Team PCT = Psychological Commitment to the Team FFL = Level of Interest of Professional Football. + p < .10. * p < .05. ** p < .01. *** p < .001. Table 3 Hierarchical Regression Analysis of the Number of Years as Fan of Favorite Team (N=151) Source df [DELTA][R.sup.2] B-wt F Step 1 Gender 1,149 .217 *** 41.38 *** Step 2 Gender FFL 2,148 .026 * 23.85 *** Step 3 Gender -5.19 *** FFL .66 * Self-Monitoring .0.19 + -.10 + (Constant) 3,147 18.76 17.46 *** R = .51 [R.sup.2] = .26 adj [R.sup.2] = .25 Note. FFL = Level of Interest in Professional Football. + p < .10. * p < .05. ** p < .001. *** p < .001 Table 4 Hierarchical Regression Analysis of the Number of Favorite Teams (N=151) Source df [DELTA][R.sup.2] B-wt F Step 1 Gender 1.149 .003 *** 0.50 Step 2 Gender FFL 2,148 .034 * 2.89 + Step 3 Gender .43 + FFL .11 * Self-Monitoring .90 *** .05 *** (Constant) 3,147 -1.66 7.18 *** R = .36 [R.sup.2] = .13 adj [R.sup.2] = .11 Note. FFL = Level of Interest in Professional Football. + p < .10. * p < .05. ** p < .01. *** p < .001. Table 5 Hierarchical Regression Analysis of Psychological Commitment to Team (N=151) Source df [DELTA][R.sup.2] B-wt F Step 1 Gender 1.149 .108 *** 17.96 *** Step 2 Gender FFL 2,148 .125 * 22.48 *** Step 3 Gender -4.74 + FFL 2.98 *** Self-Monitoring .008 -.15 (Constant 3,147 51,49 15.54 *** R = .49 [R.sup.2] = .24 adj [R.sup.2] = .23 Note. FFL = Level of Interest in Professional Football. + p < .10. * p < .05. ** p < .01. *** p < .001.
Received: May 1999
[C] 1999 Winthrop Publications Limited.
Ajzen, I., Timko, C., & White, J.B., (1982), 'Self-monitoring and the attitude behavior relation'. Journal of Personality and Social Psychology, 42, pp. 426-435.
Antonen, M., (1995, May 4), 'Cheap seats, giveaways not enough'. USA TODAY, pp. C1-C2.
Backman, S.J., (1991), 'An investigation of the relationship between activity loyalty and perceived constraints'. Journal of Leisure Research, 23, pp. 332-344.
Backman, S.J., & Crompton, J.L., (1991), 'The usefulness of selected variables for predicting activity loyalty'. Leisure Sciences, 13, pp. 205-220.
Bagozzi, R.P., (1992), 'The self-regulation of attitudes, intentions, and behavior'. Social Psychology Quarterly, 55, pp. 178-204.
Calder, B.J., Phillips, L.W., & Tybout A.M., (1981), 'Designing research for application'. Journal of Consumer Research, 8, pp. 197-207.
Churchill, G.A., Jr., (1979), 'A paradigm for developing better measures of marketing constructs'. Journal of Marketing Research, 16, pp. 64-73.
Cialdini, R.B., Borden, R.J., Thorne, A., Walker, M.R., Freeman, S., & Sloan, L.R., (1976), 'Basking in reflected glory: Three (football) field studies'. Journal of Personality and Social Psychology, 34, pp. 366-375.
Cohen, J., & Cohen, P., (1975), 'Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences'. Hillsdale, New Jersey: Lawrence Erlbaum.
Crosby, L.A., & Taylor, J.R., (1983), 'Psychological commitment and its effect on post-decision evaluation and preference stability among voters'. Journal of Consumer Research, 9, pp. 413-431.
Darley, W.K., & Lim, J., (1992), 'The effect of consumer's emotional reactions on behavioral intentions: The moderating role of personal relevance and self-monitoring'. Psychology & Marketing, 9, pp. 329-346.
Day, G.S., (1969), 'A two dimensional concept of brand loyalty'. Journal of Advertising Research, 9, pp. 29-35.
DeBono, K.G., & Harnish, R.J., (1988), 'Source expertise, source attractiveness, and the processing of persuasive information: A functional approach'. Journal of Personality and Social Psychology, 55, pp. 541-546.
DeBono, K.G., & Packer, M., (1991), 'The effects of advertising appeal on perceptions of product quality'. Personality and Social Psychology Bulletin, 17, pp. 194-200.
DeBono, K.G., & Snyder, M., (1989), 'Understanding consumer decision making processes: The role of form and function in product evaluation'. Journal of Applied Social Psychology, 19, pp. 416-424.
Dick, A.S., & Basu, K., (1994), 'Customer loyalty: Toward an integrated concept of brand loyalty'. Journal of Academy of Marketing Science, 22, pp. 99-113.
Eitzen, D.S., & Sage, G.H., (1997), Sociology of North American sport (6th ed.). Dubuque, IA: Brown & Benchmark.
Friedman, H.S., & Miller-Herringer, T., (1991), 'Nonverbal display of emotion in public and private: Self-monitoring, personality, and expressive cues'. Journal of Personality and Social Psychology, 61, pp. 766-775.
Fulks, D.L., (1996), 'Revenues and expenses of Division I and II intercollegiate athletic programs: Financial tends and relationships - 1995'. Overland Park, Kansas: National Collegiate Athletic Association.
Gantz, W., & Wenner, L.A., (1991), 'Men, women, and sports: Audience experiences and effects'. Journal of Broadcasting & Electronic Media, 35, pp. 233-243.
Graeff, T.R., (1996), 'Image congruence effects on product evaluations: The role of self-monitoring and public/private consumption'. Psychology & Marketing, 13, pp. 481-499.
Haugtvedt, C.P., & Petty, R.E., (1992). 'Personality and persuasion: Need for cognition moderates the persistence and resistance of attitude changes'. Journal of Personality and Social Psychology, 63, pp. 308-319.
Haugtvedt, C.P., & Wegener, D.T., (1994), 'Message order effects in persuasion: An attitude strength perspective'. Journal of Consumer Research, 21, pp. 205-218.
Hirt, E.R., Zillman, D., Erickson, G.A., & Kennedy, C., (1992), 'Costs and benefits of allegiance: Changes in fans' self-ascribed competencies after team victory versus defeat'. Journal of Personality and Social Psychology, 63, pp. 724-738.
Howard, D.R., (1999), 'The changing fanscape for big-league sports: Implications for sport managers'. Journal of Sport Management, 13, pp. 78-91.
Jacoby, J., & Chestnut, R.W., (1978), 'Brand Loyalty: Measurement and Management'. New York: Wiley.
Jenkins, J.M., (1993), 'Self-monitoring and turnover: The impact of personality on intent to leave'. Journal of Organizational Behavior, 14, pp. 83-91.
Kraus, S.J., (1995), 'Attitudes and the prediction of behavior: A meta-analysis of the empirical literature'. Personality and Social Psychology Bulletin, 21, pp. 58-75.
Lennon, S.J., Davis, L.L., & Fairhurst, A., (1988), 'Evaluations of apparel advertising as function of self-monitoring'. Perceptual and Motor Skills, 66, pp. 987-996.
Mahony, D.F., Madrigal, R., & Howard, D.R., (1998), 'Using the psychological commitment to team (PCT) scale to segment customers based on loyalty'. Manuscript submitted for publication.
Mihoces, G., (1995, May 23), 'Fans fight post-strike hangover'. USA TODAY, pp. C1-C2.
Miller, M.L., & Thayer, J.F., (1989), 'On the existence of discrete classes in personality: Is self-monitoring the correct joint to carve?' Journal of Personality and Social Psychology, 57, pp. 143-155.
Miller, M.L., & Thayer, J.F., (1988), 'On the nature of self-monitoring: Relationship with adjustment and identity'. Personality and Social Psychology Bulletin, 14, pp. 544-553.
Murrell, A.J., & Dietz, B., (1992), 'Fan support of sports teams: The effect of a common group identity'. Journal of Sport and Exercise Psychology, 14, pp. 28-39.
Nesler, M.S., Tedeschi, J.T., & Storr, D.M., (1995), 'Context effects, self-presentation, and the Self-Monitoring Scale'. Journal of Research in Personality, 29, pp. 273-284.
Nunnally, J.C., & Bernstein, I.H., (1994), 'Psychometric Theory' (3rd ed.). New York: McGraw-Hill.
Olson, J.C., & Jacoby, J., (1971), 'A construct validation study of brand loyalty'. Proceedings of the American Psychological Association, 6, pp. 657-658.
Paulhus, D., (1982), 'Individual differences, self-presentation, and cognitive dissonance: Their concurrent operation in forced compliance'. Journal of Personality and Social Psychology, 43, pp. 838-852.
Pritchard, M.P., Havtiz, M.E., & Howard, D.R., (in press). 'Analyzing the commitment-loyalty link in service contexts'. Journal of the Academy of Marketing Science.
Richards, P.S., (1994), 'Religious devoutness, impression management, and personality functioning in college students'. Journal of Research in Personality, 28, pp. 14-26.
Snyder, C.R., Lassegard, M.A., & Ford, C.E., (1986), 'Distancing after group success and failure: Basking in reflected glory and cutting off reflected failure'. Journal of Personality and Social Psychology, 51, pp. 382-388.
Snyder, M., (1974), 'Self-monitoring of expressive behavior'. Journal of Personality and Social Psychology, 30, pp. 526-537.
Snyder, M., Berscheid, E., & Glick, P., (1985), 'Focusing on the exterior and interior: Two investigations of the initiation of personal relationships'. Journal of Personality and Social Psychology, 48, pp. 1427-1439.
Snyder, M., & DeBono, K.G., (1985), 'Appeals to image and claims about quality: Understanding the psychology of advertising'. Journal of Personality and Social Psychology, 49, pp. 586-597.
Snyder, M., & Gangestad, S., (1986), 'On the nature of self-monitoring: Matters of assessment, matters of validity'. Journal of Personality and Social Psychology, 51, pp. 125-139.
Snyder, M., Gangestad, S., & Simpson, J.A., (1983), 'Choosing friends as activity partners: The role of self-monitoring'. Journal of Personality and Social Psychology, 45, pp. 1061- 1072.
Snyder, M., & Simpson, J.A., (1984), 'Selfmonitoring and dating relationships'. Journal of Personality and Social Psychology, 47, pp. 1281-1291.
Snyder, M., & Tanke, E.D., (1976), 'Behavior and attitude: Some people are more consistent than others'. Journal of Personality, 44, pp. 501-517.
Stewart, A., & Carley, L., (1984), 'Personality characteristics of extreme scores on the self-monitoring scale'. Perceptual and Motor Skills, 58, pp. 199-205.
Wakefield, K.L., (1995), 'The pervasive effects of social influence on sporting event attendance'. Journal of Sport and Social Issues, 19, pp. 335-351.
Wakefield, K.L., & Sloan, H.J., (1995), 'The effects of team loyalty and selected stadium factors on spectator attendance'. Journal of Sport Management, 9, pp. 153-172.
Yardley, J., (1998, February), 'The larger significance of Michael Jordan'. Sky, pp. 46-50.
Zanna, M.P., Olson, J.M., & Fazio, R.H., (1980), 'Attitude-behavior consistency: An individual difference perspective'. Journal of Personality and Social Psychology, 38, pp. 432-440.
Zillman, D., Bryant, J., & Sapolsky, B.J., (1989), 'Enjoyment for sport spectatorship'. In J.H. Goldstein (ed.), Sports, Games, and Play: Social and Psychological Viewpoints (2nd ed.) (pp. 241-278). Hillsdale, New Jersey: Lawrence Erlbaum.
Zillman, D., & Paulus, P.B., (1993), 'Spectators: Reactions to sports events and effects on athletic performance'. In R.N. Singer, M. Murphey, & L. Tennant (eds.), Handbook of Research on Sports Psychology (pp. 600-619). New York: MacMillan.
Zyto-Sitkiewcz, D., (1991), 'Dlaczego przychodia? Psychologiczna interpretacja motywagi kibicowania' (Why do they come? A psychological interpretation of a sports fan's motivation). Kultra Fizycyzna, 45, pp. 8-9. (From Sports Discus Abstracts, Abstract No. 299316).
Daniel F. Mahony is an Assistant Professor and the Director of the Sport Administration Program at the University of Louisville. He has previously published articles in a variety of academic journals including Journal of Sport Management, Journal of Sport and Social Issues, Sport Management Review, Sport Marketing Quarterly, and International Sports Journal.
Prof Robert Madrigal's research interests focus on fan behavior. He is particularly interested in the nature of the fan experience and how spectators "consume" a sports performance. Dr. Madrigal has also investigated how fans' attachment to a preferred team influence their perceptions of sports sponsorship.
Dennis Howard is a professor of marketing at the University of Oregon's Warsaw Sports Marketing Center. He is former head of the Graduate Program of Sport Management at the Ohio State University. He is best known for his work in the areas of sport finance and fan loyalty. He has co-authored three books and close to 100 articles in sport and leisure management/marketing publications.
Daniel F. Mahony, Ph.D.
Department of HPES
106 HPES/Studio Arts Building
University of Louisville
Louisville, Kentucky 40292
Tel: (502) 852-5040
Fax: (502) 852.6683
Robert Madrigal, Ph.D.
Department of Marketing Warsaw Sports Marketing Center, Lundquist College of Business
University of Oregon
Eugene, Oregon 97403-1208
Tel: (541) 346-5163
Fax: (541) 346-3341
Dennis Howard, Ph.D. Professor
Department of Marketing
Warsaw Sports Marketing Center
Lundquist College of Business
University of Oregon
Eugene Oregon 97403-1208
Tel: (541) 346-3352