The impact of cause-related marketing (CRM) in ...

Copyright © eContent Management Pty Ltd. Journal of Management & Organization (2010) 16: 515–527.

The impact of cause-related marketing (CRM) in spectator sport KI TAK KIM Paichai University, Daejeon, South Korea

DAE HEE KWAK University of Michigan, Ann Arbor, MI, USA

YU KYOUM KIM The Florida State University, Tallahassee, FL, USA

ABSTRACT Cause-related marketing (CRM) refers to the marketing strategy an organization uses to associate itself with a good cause. Even though CRM decisions may be partly charitable, they may also serve corporate self-interest. Although this area of inquiry is growing, CRM’s strategic potential as an effective management tool for connecting sport organizations (i.e., teams) with consumers has not been thoroughly examined in a sport management context. In order to provide an improved picture of spectator sport consumers’ perceptions toward a sport team’s CRM initiatives, we developed a structural model that incorporates perceived CRM, attitudes toward the team, and re-attendance intention. Using LISREL analysis, the findings showed that CRM’s effect on re-attendance intention was completely mediated through the attitude toward the team. In addition, perceptions toward the team’s motive for CRM did not vary CRM’s effect on attitude and behavioral intention. The lack of interaction effect might provide evidence that there may be universal appeal and effectiveness of CRM in a spectator sport context. Consequently, the findings provide a useful rationale for making managerial decisions about implementing and maintaining CRM efforts in sport organization. Keywords: corporate social responsibility, cause-related marketing, sport consumption

D

ue to growing public concern over social and ecological issues, many organizations wish to develop synergy between business and philanthropic acts (Kukalis, 2009; McAlister & Ferrell, 2002). Associating organizations with good causes has become attractive to many businesses, and particularly for those in the sport industry (Cregan, 2008). In particular, a growing body of literature has suggested that cause-related marketing (CRM) programs are reported to enhance company image (Rigney & Steenhuysen, 1991), improve favorable attitudes and beliefs toward Volume 16, Issue 4, September 2010

sponsoring companies (Becker-Olsen, Cudmore, & Hill, 2006; Ross, Stutts, & Patterson, 1991), and increase purchase intentions (Becker-Olsen et al., 2006). Further, from an organizational standpoint, CRM efforts could place an organization in a competitive position over longer time period (Brammer & Millington, 2008). Despite CRM’s strategic potential as a viable management tool and its apparent appeal to organizations and consumers (Berger, Cunningham, & Kozinets, 1996; Ross, Patterson, & Stutts, 1992; Smith & Langford, 2009), the impact of CRM JOURNAL OF MANAGEMENT & ORGANIZATION

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Ki Tak Kim, Dae Hee Kwak and Yu Kyoum Kim

on consumers’ evaluations and intentions in the sport management domain has received very little attention from researchers (cf. Roy & Graeff, 2003). Therefore, this study attempts to broaden our understanding of spectator sport consumers’ perceptions toward the team’s CRM initiatives as well as their cognitive and behavioral responses to these strategic efforts. It should be noted that decisions undertaken as corporate social responsibility in the form of CRM may be partly altruistic, but they may also serve corporate self-interest (i.e., generating revenue) (Dean, 2004). In this regard, CRM is subject to the criticism that it is exploitative of the cause (Varadarajan & Menon, 1988). Even among non-profit organizations, CRM is often controversial because it overly emphasizes selfinterest and it threatens to commercialize nonprofits (File & Prince, 1998). Prior evidence has allowed researchers to suggest consumers will not necessarily accept these social causes as purely altruistic; thus, social causes may or may not actually reward the firm (Barone, Miyazaki, & Taylor, 2000; Becker-Olsen et al., 2006; Brown & Dacin, 1997; Ellen, Mohr, & Webb, 2000). Previous research raises some important questions for sport managers as well as academicians. For example: Does a team’s motive for engaging in CRM influence fans’ attitudes toward the team and loyalty? Specifically, would fans report more (less) favorable attitudes and intentions if they perceived the team’s motive for engaging in CRM as purely altruistic (profit-oriented)? Specific to a spectator sport consumption context though, little is known about whether the organization’s (i.e., team) motive for CRM changes the relationship between CRM and its effects on consumers’ evaluation and intentions. Consequently, we seek to find answers to the abovementioned questions. To answer the questions, a structural model was developed that incorporates perceived CRM, attitude toward team, and re-attendance intentions based on prior literature on social responsibility (cf. Barone, Norman, & Miyazaki., 2007; Dean, 2004) and 516

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the potential moderating effect of motive for CRM on consumers’ response to the team’s social initiatives was hypothesized. A cross-sectional survey-based research design was used for the empirical investigation. The measurement model was tested using confirmatory factory analysis and the relationships in the hypothesized model were tested using simultaneous equations and multiple group analysis.

LITERATURE REVIEW Cause-related marketing According to Varadarajan and Menon (1988), CRM is the process of marketing activities that link a firm’s contributions to a charitable cause to a revenue-producing transaction with the firm that satisfies both business and individual objectives. Although most researchers would agree that CRM is a firm’s commitment to a social cause in lieu of consumer purchases (Varadarajan & Menon, 1988), others contend that it is simply another form of corporate philanthropy which involves marketing objectives such as increased revenues (DiNitto, 1989). Even though the initial application of CRM was focused on increasing short-term sales while ‘doing good,’ companies are increasingly employing CRM as part of their long-term strategy to build customer relationships, differentiate their products from competitor’s offerings, and enhance corporate image (Varadarajan & Menon, 1988). Since the advent of CRM in the early 1980s, the use of CRM as a marketing platform has been gradually adopted by companies because they have come to recognize that consumers value corporate support of social causes (Cone, Feldman, & DaSilva, 2003; Roy & Graeff, 2003). Corporate expenditures for CRM campaigns have also increased dramatically with firms now going to greater lengths to search for opportunities that demonstrate their unique commitment to social issues (Roy & Graeff, 2003). For instance, the IEG1 sponsorship report revealed data about how Volume 16, Issue 4, September 2010

The impact of cause-related marketing (CRM) in spectator sport

firms invested $1.44 billion on CRM sponsorships and activation in 2007; this is an 80 percent increase since 2001 (Poole, 2007). Evidence from the IEG sponsorship report clearly demonstrates how CRM is an exceedingly fast growing sector of sponsorship. In sports, teams and leagues have been embracing new forms of social consciousness to become a good citizen in their respective community (Aschermann, 2006). In particular, CRM is being employed by many sport properties as a way of community engagement; this is a way for the sport property to give back to their home community and forge a stronger bond between them and their target markets (Roy & Graeff, 2003). For example, the National Football League (NFL) has a longstanding and highly promoted relationship with United Way while the Professional Golf Association (PGA) Tour raises millions of dollars for designated charities at each local tour destination (Lombardo, 2008). In 2005, The National Basketball Association (NBA) also launched the NBA Cares campaign, which is specifically focused on community service involvement. Through the NBA Cares initiative, league partners, executives, team officials, and players have become involved in a variety of charity programs (i.e., Habitat for Humanity and Project Rebound) (Lombardo, 2008). Even so, there remains a growing need for sport organizations and athletes to be more effectively engaged in social causes. In their telephone survey, Roy and Graeff (2003) examined consumer attitudes toward professional athletes/teams and found consumers have very high expectations for professional athletes and teams to be involved in their local communities. In support of this, Irwin, Lachowetz, Cornell, and Clark (2003) found that a non-profit organization involved with CRM had a positive influence on sport consumers’ attitudes, beliefs, and purchase intentions 1

toward the sponsoring company (such as a sport team or league).

Consumer responses to CRM programs Previous research following consumer responses to CRM initiatives has tended to focus on the description of general responses to the concept of CRM and the measurement of how the elements of CRM campaigns affect attitudes and purchase intentions (Webb & Mohr, 1998). Researchers have also found evidence suggesting people generally believe CRM is a good way to raise money for social causes (Ross et al., 1991, 1992). A specific line of empirical research has allowed sport marketers to suggest that consumers’ perceived CRM is associated with favorable consumer attitudes toward the respective firm (Berger et al., 1996; Irwin et al., 2003; Lavack & Kropp, 2003; Ross et al., 1991, 1992), and corresponding purchase decisions (Berger et al., 1996; Irwin et al., 2003). Based on these findings, there is enough evidence for researchers to infer that, generally speaking, consumers express favorable attitudes and intentions when asked to evaluate a firm engaging in CRM initiatives. Therefore, it could be expected that in the spectator sport context, perceived CRM might have positive influence on attitude toward the organization (i.e., team) and intention to re-attend the event.

Moderating role of perceived motivation for CRM Although it is a generally accepted assumption that consumers will reward firms engaging in social initiatives, there is some evidence to the contrary. A counter-position has been taken by several researchers who argue it is unlikely these social initiatives always lead to favorable consumer evaluation (Becker-Olsen et al., 2006; Drumwright, 1996; Mohr, Webb, & Harris,

IEG is known as the world’s leading provider of sponsorship analysis and research. Founded in 1981, IEG annually publishes IEG Sponsorship Report, the IEG Sponsorship Sourcebook, and other industry publications and sources. For more detail, visit www.sponsorship.com.

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2001). For instance, corporate motive for CRM (cause-oriented vs. profit-oriented) may have differential outcomes on the effect of CRM on consumers (cf. Barone et al., 2007; Ellen, Mohr, & Webb, 2006; Yoon, Gürban-Canli, & Schwarz, 2006). Simply put, CRM does not automatically guarantee a favorable evaluation. Researchers have suggested the underlying motive for a firm’s use of CRM can result in consumers’ perceiving the company’s efforts as either cause-beneficial or cause-exploitative (cf. Drumwright, 1996), though previous research about consumer attributions toward CRM has yielded mixed results (Dean, 2004). For example, Ross et al. (1992) measured consumer attitude toward a real-life CRM campaign that was communicated via a Proctor & Gamble advertisement. This ad stated to the public that Proctor and Gamble would donate 10 cents to the Special Olympics for every coupon redeemed for Proctor & Gamble products. In this study, participants did not perceive the campaign to be exploitative of the cause; most participants perceived the firm was executing the campaign in a socially responsible manner. Conversely, in a study by Webb and Mohr (1998) they found a split-decision with their participants regarding CRM. Herein, half of their respondents attributed an egotistic interest to firms engaged in CRM, while the other half recognized that at least some part of firm motivation was altruistic. Given how a consumer’s attribution toward corporate motive for CRM can vary, it seems plausible that the consumer’s perceived motive for CRM might also have differential effects toward their attitudes and purchase intentions. When motives for CRM are considered profitoriented, evaluations toward firms are likely to diminish. However, when motives are considered to be cause-oriented and altruistic, evaluations toward firms are likely to be enhanced (cf. Becker-Olsen et al., 2006). Once again, conflicting results have been noted, this time in the social responsibility literature concerning the moderating effect of perceived CRM motive on 518


consumer evaluations. For instance, Gupta and Pirsch (2006) examined the influence of consumers’ skepticism about a company’s motivation for participating in a CRM initiative; they found motivation was not associated with consumers’ purchase decisions. On the other hand, researchers also report CRM is moderated by consumer perceptions of the company’s motive for engaging in CRM (Barone, et al., 2007). Similarly, Ellen et al. (2006) found evidence supporting the idea that company evaluations were positively affected by attributions of altruism (i.e., cause-centered). Purchase intention was also affected by these same attributions as well as being negatively affected by egotistic (i.e., profit-centered) attributions. Regrettably, little is known about how a team’s motive for CRM moderates the effects of the CRM initiatives on fans’ team evaluations and re-attendance intentions in a spectator sport context.

METHOD Participants and procedures Prior to collecting any data, potential participants were informed that their contribution to the study was completely voluntary. They were then asked to fill out an informed consent form. After participants agreed to take part in the study, they were next given a brief explanation of the researcher objectives for the study as well as detailed instructions about filling out the questionnaire. Participants did not receive monetary compensation for participating in the study. On average, the survey took 10 min to complete. A total of 326 spectators at a professional baseball game in a Metropolitan city in Korea participated in the study. Sixteen surveys were deemed unusable due to invalid responses (e.g., blank, double answers, etc.) and were therefore eliminated from the sample. This left the researchers with a total of 310 usable responses. Of the remaining 310 participants, 31% were male and 69% were female. The participants ranged in age from 18 to 53 years (M = 28.92, SD = 8.15). Approximately half of Volume 16, Issue 4, September 2010


the participants reported that they had annual incomes that were greater than $40,000.

Instrumentation First, only items that had shown good psychometric properties in the past research were utilized. Second, these selected items underwent an additional review and were modified to support the purpose of the current study. Third, a panel of experts consisting of five scholars and two practitioners in sport management examined the items for content validity. The resultant questionnaire consisted of four main components: (1) CRM, (2) attitude toward the team, (3) motive for CRM, and (4) re-attendance intention. To measure perceived CRM, three items from Maignan (2001) were used and modified. Next, to measure attitudes toward the team, four items from Madden, Allen, and Twible (1988) were modified to suit the research purposes. Additionally, one item from each of Johnson and Grayson (2005), Garbarino and Johnson (1999), Fournier (1998), and Lacey, Suh, and Morgan (2007) were modified to measure re-attendance intention. Lastly, one item was adopted and modified from BeckerOlsen et al. (2006): ‘I think the team’s motivation for social responsibility initiatives are their sincere interest in developing community and society.’ All of the items were measured using a seven-point Likert-type scale; response format ranged from strongly disagree (1) to strongly agree (7).

Data analysis Before conducting main analyses, the data was tested to ensure it reasonably meet the essential assumptions for structural equation modeling (SEM) techniques used in the current study. Linearity of the observed variables was probed by graphically assessing randomly selected pairs from the scatter plot made available through SPSS 16.0 (SPSS, 2005). Extreme multicollinearity or singularity was tested in the data by evaluating the determinant of the input matrix. Univariate normality of the observed variables was assessed using descriptive statistics (i.e., skewness and kurtosis). Volume 16, Issue 4, September 2010

Moreover, multivariate normality was assessed using Mardia’s (1985) multivariate skewness and kurtosis coefficients. These were available through PRELIS 2.80 (Jöreskog, & Sörbom, 2006). A confirmatory factor analysis (CFA) was conducted to evaluate the measurement model using Mplus 5.2 program (Muthén & Muthén, 2008). The formula of χ2/df was used to assess the overall fit of the model. The comparative fit index (CFI), the standard root-mean-squared residual (SRMR), and the root-mean-square error of approximation (RMSEA) all followed Weston and Gore’s recommendation (2006). Hu and Bentler (1999) suggested a cutoff-value close to 0.95 or higher for CFI in combination with a cutoff-value close to or less than 0.09 for SRMR. Brown and Cudeck (1992) noted that RMSEA values of less than 0.06 indicate good fit, values of 0.08 or less would represent reasonable fit and values higher than 0.10 indicate poor fit (Brown & Cudeck, 1992). Average variance extracted (AVE) values were used to assess how well the items on a specific subscale accounted for the underlying construct’s variance. AVE values above 0.50 indicate that the items collectively explain the adequate amount of variance in the underlying construct (Hair, Black, Babin, Anderson, & Tatham, 2005). Discriminant validity of each construct was tested by performing multiple χ2 difference tests of unity between all pairs of constructs (Anderson & Gerbing, 1988). For estimation of scale reliability, a SEM method developed by Raykov (1997, 2001) was used to offset limitations of Cronbach’s coefficient alpha (Cronbach, 1951). Simultaneous equations were performed using Mplus 5.2 to test the hypothesized model that specified direct paths from CRM to Attitude and Re-Attendance Intention, and an indirect path from CRM through Attitude to Re-Attendance Intention. Next, a comparison was made between the model with cross-group equality constraints on a causal path coefficient (γs) to a model without crossgroups equality on a causal path coefficient (γs). This was done to test the moderating effect of motive for team’s CRM on the hypothesized relationships JOURNAL OF MANAGEMENT & ORGANIZATION

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among the constructs (Kline, 2005). The comparison of the path coefficients to test interaction effect requires measurement invariance. According to Meredith (1993), there are three levels of measurement invariance: (1) weak factorial invariance (same factor loadings for each observed variable across categories), (2) strong factorial invariance (same factor loadings and intercepts), and (3) strict factorial invariance (same factor loadings, intercepts, and error variance). Strong and strict factorial invariance are not necessary to test interaction effects of categorical variables on the relationship between latent exogenous variables and latent endogenous variable (Vandenberg & Lance, 2000). Thus, prior to comparison of path coefficients, weak factorial invariance was tested by comparing a model that specified the unstandardized factor loadings for the observed variables to be equal across levels of motive for team’s CRM with a model that set unstandardized factor loadings to be free across the categories (Kline, 2005). For this multiple group analysis, the participants were divided into three groups based on rating of motive for team’s CRM. Twenty-two percent of the participants who responded 1 through 3 were placed into the low group, 36% of participants

who responded 4 were placed into the neutral group, and 42% of participants who responded 5 through 7 were put into the high group.

RESULTS Evaluation of assumptions The total of 310 cases is greater than the recommended minimum sample size of 200 (Weston & Gore, 2006). In addition, the ratio of cases to observed variables was 28:1, which seemed to be adequate for the following SEM analyses (Bollen, 1989; Kline, 2005). Table 1 shows the correlations, means, and standard deviations among variables. All randomly selected pairs of observed variables demonstrated a linear relationship. The assumption can also be made that there was no extreme multicollinearity or singularity because of the determinant of input matrix non-zero, positive value. However, the data failed to meet both univariate and multivariate normality assumption. Eight observed variables were significantly skewed (p < 0.01) and five observed variables revealed significant kurtosis (p < 0.01). In addition, Mardia’s Normalized Coefficient of both skewness

TABLE 1: CORRELATIONS AMONG VARIABLES Variables

1

CRM1

1.00

CRM2

0.70

1.00

CRM3

0.57

0.67

1.00

Attitude1

0.42

0.36

0.36

1.00

Attitude2

0.34

0.33

0.34

0.79

1.00

Attitude3

0.40

0.36

0.29

0.74

0.73

1.00

Attitude4

0.36

0.31

0.31

0.67

0.72

0.76

1.00

Attendance1

0.32

0.29

0.28

0.51

0.52

0.54

0.55

1.00

Attendance2

0.35

0.26

0.25

0.51

0.51

0.53

0.54

0.83

1.00

Attendance3

0.35

0.28

0.26

0.47

0.45

0.52

0.51

0.76

0.77

1.00

Attendance4

0.36

0.36

0.29

0.50

0.47

0.54

0.53

0.68

0.68

0.69

1.00

Mean

4.31

4.11

4.27

5.16

5.35

5.41

5.32

5.86

5.80

5.71

5.35

SD

1.43

1.39

1.44

1.46

1.34

1.38

1.40

1.09

1.11

1.29

1.26

520

2

3

4

5


6

7

8

9


10

11


(z = 22.33) and kurtosis (z = 14.85) were significant (p < 0.01). To alleviate the potential problems associated with the non-normality, Satorra and Bentler’s (1994) scaling method was employed.

discriminant validity (Anderson & Gerbing, 1988). Altogether, these results allow for the researchers to provide evidence that the instrument used in this study measured the constructs of interest with strong reliability and validity.

Measurement model The input correlation matrix for the measurement model and the subsequent analyses was reported in Table 2 following McDonald and Ho’s (2002) recommendation on reporting results from SEM analyses. As indicated by Satorra–Bentler scaled χ2 (S–B χ2)/df = 70.25/41 = 1.71, CFI = .99, SRMR = 0.03, and RMSEA = 0.05, the measurement model fit the data well. Table 2 displays factor loadings, reliability coefficients, and AVE values. All factor loadings were positive and significant (p < 0.01) ranging from 0.75 to 0.91. All reliability coefficients were higher than the recommended criteria of 0.70 (Kline, 2005) and all AVE values were higher than the suggested cutoff criteria of 0.50 (Hair et al., 2005). Finally, all pairs of construct showed a correlation coefficient that was significantly different from 1.0, indicating

Structural model The hypothesized model specifying the structural relationships among CRM, Attitude, and Re-Attendance Intention fit the data well (S–B χ2 /df = 70.25/41, CFI = 0.99, SRMR = 0.03, RMSEA = 0.05). Figure 1 displays the path coefficient estimates of the model. The direct path from CRM to Attitude was significant (standardized γ = 0.49, S.E. = 0.06) and the direct path from Attitude to Re-Attendance Intention was also significant (standardized β = 0.63, S.E. = 0.05). The indirect effect of CRM on Re-Attendance Intention was significant, (standardized γ = 0.31, S.E. = 0.05) indicating the strength of mediated path from CRM to Re-Attendance Intention was significantly larger than direct path from CRM to

TABLE 2: SUMMARY RESULTS FOR CONFIRMATORY FACTOR ANALYSIS Factors and items

ë

S.E.

Perceived CRM The team participates in the management of public affairs

0.80

0.04

The team allocates some of their resource to philanthropic activities

0.88

0.04

The team plays a role in our society that goes beyond the. mere generation of profit

0.75

0.04

Attitude The team A is favorable.

0.86

0.02

The team A is valuable.

0.87

0.02

The team A is enjoyable.

0.87

0.02

The team A is attractive.

0.83

0.03

Attendance intention The team A’s game will be my choice if I consider attending a sporting event.

0.91

0.02

I will spend my time and money to enjoy team A’s game again.

0.91

0.02

The likelihood I will attend Team A’s game in the future is high.

0.85

0.04

I would recommend others to attending the team’s game.

0.77

0.03


ñ

AVE

0.90

0.66

0.93

0.74

0.93

0.74


521


Re-Attendance Intention. However, as shown in Figure 1, direct path from CRM to Re-Attendance Intention was not significant while statistically partitioning out Attitude (standardized γ = 0.10, S.E. = 0.06). Taken together, the results indicate that there was a complete mediation from CRM through Attitude to Re-Attendance Intention (Iacobucci, Saldanha, & Deng, 2007).

Test of moderating effect Table 3 presents the results of a series of χ2 difference tests for evaluating measurement invariance and the moderating effect of perceived motive for team’s CRM. The model freely estimates the factor loadings across three groups, but it did not fit the data significantly better than the model specifying the same factor loadings across the groups, Δ S–B χ2 (16) = 19.48, p > 0.05. This indicates the measurement structure was stable

Attitude .64*

.49*

Perceived CRM

.10

Re-Attendance Intention

Note. Parameter estimates are standardized coefficients (*p < .05).

FIGURE 1: STRUCTURAL MODEL FOR PERCEIVED CRM, TEAM IMAGE, AND RE-ATTENDANCE INTENTION.

regardless of perceived motive level. All three models constraining one direct path to be same across the three groups fit the data as equally well as the model freely estimating all the paths across the groups (path from CRM to Attitude: Δ S–B χ2 (2) = 0.24, p > 0.05; path from Attitude to Re-Attendance Intention: Δ S–B χ2 (2) = 1.48, p > 0.05; path from CRM to Re-Attendance Intention Δ S–B χ2 (2) = 2.03, p > 0.05). This provides evidence that there was not a moderating effect of perceived motive for team’s CRM on any relationships among the constructs in the model.

DISCUSSION The purpose of this study was to examine the structural relationships among perceptions of CRM, attitudes toward the team and re-attendance intention, and how the perceived motive for a team’s CRM moderates decision-making processes for reattendance in sport events. Overall, the presented conceptual model explained a total of 47% of variance in re-attendance intention. This is large for social science research (Cohen, 1988). As expected, the results also showed that the perceived CRM significantly influenced attitudes toward a team, explaining 24% of the variance. This is consistent with the previous literature that CRM positively affects attitude towards organizations (Berger et al., 1996; Brown & Dacin, 1997; Irwin et al., 2003; Ross et al., 1991, 1992; Yoon et al., 2006).

TABLE 3: INVARIANCE TESTS OF STRUCTURAL MODEL FOR PERCEIVED CRM, ATTITUDE, AND RE-ATTENDANCE INTENTION Model

Goodness of fit

M1: Unconstrained

S–B χ2 (139) = 177.27, p < 0.01 –

M2: Equal factor loadings

S–B χ2 (155) = 196.97, p < 0.01 M2–M1: S–B χ2 (16) = 19.48, p > 0.05

M3: Equal factor loadings and equal path from CRM to attitude

S–B χ2 (156) = 196.89, p < 0.01 M3–M2: ΔS–B χ2 (1) = 0.24, p > 0.05

M4: Equal factor loadings and equal path from attitude to re-attendance intention

S–B χ2 (156) = 198.61, p < 0.01 M4–M2: ΔS–B χ2 (1) = 1.48, p > 0.05

M5: Equal factor loadings and equal path from CRM to re-attendance intention

S–B χ2 (156) = 199.03, p < 0.01 M5–M2: ΔS–B χ2 (1) = 2.03, p > 0.05

522


Test of invariance



Attitudes toward a team significantly affected the re-attendance intention (explaining 40% of variance in re-attendance intention). Once more, this result confirmed past research showing a positive relationship between the attitude toward an organization and the intention or actual behavior to purchase the products of the organization (Brown & Stayman, 1992; Chaudhuri & Holbrook, 2001; Dick & Basu, 1994; Lafferty & Goldsmith, 1999; Morgan & Hunt, 1994). From an organizational standpoint, the findings of this study support the notion that CSR efforts can yield a number of commercial benefits (Smith & Langford, 2009). According to Smith and Langford (2009), organizational benefits of engaging in CRM include enhanced corporate reputation, consumer acquisition, and increased purchase intent. Our findings are congruent with these findings, showing that CRM efforts can provide competitive advantages to a spectator sport team by enhancing consumers’ attitude toward the team and repurchase intentions (cf. Irwin et al., 2003). Numerous conceptual frameworks concerning the decision-making process assume that the consumers pass through a sequence of psychological steps to reach their decision. For example, Lavidge and Steiner (1961) proposed a hierarchical model of advertising effectiveness. In this model, they hypothesized seven different stages leading to purchase behavior; consequently, the hierarchy-of-effects concept has played a large part of developing consumer behavior research (MacInnis & Jaworski, 1989; MacKenzie & Lutz, 1989). Despite a variety of hierarchical models that exist to explain consumer behavior, the basic hierarchical pattern still remains in most models. The hierarchy is a progression through certain psychological stages. One implication from this is the earlier stages are necessary preconditions for later stages. Correspondingly, the results from this study broadly support the widely accepted hierarchy proposition mentioned above. Herein, CRM explained a total 17% of variance in re-attendance intention, although, CRM’s effects on re-attendance intention were completely Volume 16, Issue 4, September 2010

mediated through the attitude toward the team. This indicates that CRM was not the direct cause of re-attendance intention. However, it was a major facilitator which helped the spectator pass through a critical psychological stage (e.g., forming a positive attitude) to reach the behavioral intention. A significant relationship among CRM, attitude toward the team, and re-attendance intention was established in the current study. With this knowledge in hand, the nature of association among the constructs and whether or not they would differ by perceived motive for the team’s CRM initiatives was explored. The strength of the associations among CRM, attitude toward the team, and re-attendance intention did not vary with the level of perceived motive for the team’s CRM. On the one hand, this result is inconsistent with the previous research findings about how CRM’s effect on attitude and purchase intention would diminish when the consumers perceived the organization’s intent for CRM was profit-centered and self-oriented rather than cause-centered and altruistic (Barone et al., 2007; Becker-Olsen et al., 2006; Drumwright, 1996; Ellen et al., 2000). On the other hand, the results are consistent with a study by Gupta and Pirsch (2006) who showed that consumers’ skepticism about the company’s motivation for participating in a CRM initiative was not associated with their purchase decisions. Thus, the failure to detect an interaction effect may imply universal appeal and effectiveness of CRM in a spectator sport context, regardless of the team’s motive for CRM. One possible explanation for the non-significant moderating effect is that it might reflect a consumer’s sophistication about CRM as a marketing tool. The previous studies that found the moderating effect of the motivation for CRM typically suggested that CRM is effective only when the firm’s self-oriented motivation is disguised (Barone et al., 2007; Becker-Olsen et al., 2006; Drumwright, 1996; Ellen et al., 2000). In some cases, the consumers might be sophisticated enough (have an adequate level of awareness/prescience) to discern how the motivation for a firm’s activities may be JOURNAL OF MANAGEMENT & ORGANIZATION

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inherently profit-oriented to a certain extent, but still accept the business principle quite comfortably. Therefore, low to moderate levels of perceived motive might not diminish CRM’s effect on attitude and consumption because the consumers may still positively evaluate the firm or brand that, at a minimum, at least pretends to care for the consumers and the community. Another possible explanation for the nonsignificant result is the unique psychographic characteristics of sport fans when compared to general consumers (such as high identification and strong relationship quality with the sport team). In this study, the spectators were in the sport stadium; consequently, the respondents may have a stronger resonance for the brand (team) than the samples retained in previous studies. Furthermore, the existing sport management literature provides evidence that people who strongly identify with a sport team showed distinct behavioral patterns when compared to people who were weakly identified (Laverie & Arnett, 2000). Thus, the current findings might reflect how highly identified fans tend to be more resistant in their evaluative beliefs and judgments on the negative information (causeexploitative motive) for the team’s CRM. The lack of an interaction effect might also provide evidence that CRM is an important predictor of sport consumption behaviors regardless of the perceived motive for the team’s CRM. If so, this suggests there may be universal appeal and effectiveness of CRM in a sport context. However, this contradictory finding may also be sample specific and it should therefore be interpreted with caution. The current study has several implications for research and practice. This study serves as one of a few research efforts to develop and empirically test a theoretical model explaining the relationship among CRM, attitude and attendance in a sport context. This theoretical model has been further developed and empirically supported in this study and therefore provides researchers with a conceptual foundation for better understanding how CRM affect the sport consumption behaviors. In addition, through the research results the authors have 524


been able to demonstrate how the effect of CRM is mediated through the attitude to attendance intention. In other words, our findings add to the body of sport management literature that attendance is not a direct and immediate outcome of CRM. Evaluating and measuring effectiveness of the CRM campaign has long been a major interest in management research. The results from this study provides researchers with a deeper understanding of what might reasonably be expected as outcomes of CRM. Immediate increases in attendance were not found to be a direct outcome of CRM, though improvement in attitude was identified by the participants of this study. Therefore, enhancement of psychological mediators such as attitude, image, and relationship quality may be more suitable objectives of CRM than immediate increases in consumer attendance. Managerial decisions of investment on CRM typically rely on the fundamental belief that the CRM is capable of yielding meaningful performance outcome in return for the investment. Thus, one key implication from this study for managers is the results justified a team’s investment in CRM. This study empirically supports the widely held belief that a team’s CRM initiatives will enhance sport consumer’s attitude toward that team, eventually increasing their level of sport consumption. Moreover, the effect of CRM on attitudes toward team and sport consumption was sizable. In fact, the effect of CRM was so powerful that it is not absolutely essential for sport marketers to artificially disguise their partly self-centered and profitoriented motivation for CRM. Instead of focusing on disguising their efforts, sport teams should focus on promoting how their CRM initiatives contribute to the development of community and society. Overall, the results of this study provide a useful rationale for making managerial decisions about launching and maintaining CRM efforts in their respective sport organization. With that said, several limitations must also be noted. The data were collected from attendance at a sport event/game. The nature of this sample may limit the generalizability of the finding because the psychographic and behavioral traits of the attendees Volume 16, Issue 4, September 2010


might be different than those of non-attendees. For instance, it is possible that identification with the team might be higher for the study’s participants (i.e., attendees) than the general population. Therefore, future research efforts should control for the effect of key psychographic variables such as team identification and relationship strength. Also limiting the generalizability of the study was the selected sport, which in this case was baseball. The findings relative to the sport of baseball may not be applicable to other sports such as football, basketball, and soccer. Therefore, future research should examine a variety of sports at a variety of different competitive levels (e.g., high school, collegiate, and professional); this would enhance sport marketer’s and researchers’ ability to generalize the findings beyond one sport. Finally, this study does not claim to include all of the potential mediators from CRM effort to actual attendance. Only attitude was included as a key mediator in this research effort. Inclusion of critical mediators between CRM efforts and the sport consumption process would aid researcher understanding of this phenomenon in a sport consumption behavior context. For example, image (Keller, 1993; Ross, 2006; Roth, 1995) and relationship quality (Fournier, 1998; Palmatier, Dant, Grewal, & Evans, 2006), would be useful additions to the conceptual model, especially the latter of these two since it is considered to be a key antecedent for consumption behavior.

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Accepted 01 December 2009


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