EVALUATING THE CRISIS RESPONSE STRATEGIES OF A UNIVERSITY BASKETBALL PROGRAM: HOW DO REACTIONS DIFFER BASED ON APOLOGIES, CRISIS SEVERITY, AND TEAM IDENTIFICATION? By Thomas E. Isaacson A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Communication 2012 ABSTRACT EVALUATING THE CRISIS RESPONSE STRATEGIES OF A UNIVERSITY BASKETBALL PROGRAM: HOW DO REACTIONS DIFFER BASED ON APOLOGIES, CRISIS SEVERITY, AND TEAM IDENTIFICATION? By Thomas E. Isaacson Negative news about collegiate sports teams in the United States is nearly unavoidable for most universities. The sheer number of athletes involved in multiple programs at major universities increases the likelihood of problems. American football programs alone include rosters of 100 or more players, and the total number of athletes at National Collegiate Athletic Association (NCAA) member institutions in the United States is over 360,000. Recent highprofile crises at Penn State, Ohio State, and University of Miami provide examples of the diverse types of crises that can happen to a program and illustrate the importance of appropriate university responses. However, once the crisis has happened little is known about the impact it will have on target audiences and more research is required to aid in the development of evidence-based recommendations. Of particular importance to a university’s athletic department are the future behavioral intentions of its fans. Will the crisis impact fans’ support of the university’s athletic programs? Decreased support could impact attendance, TV viewing, merchandise sales, or university donations. Research from the public relations field on crisis communication provides an approach to studying crisis response strategies. Specifically, the Situational Crisis Communication Theory (SCCT) categorizes the responses and recommends when each should be used. This dissertation manipulates crisis response strategies and crisis severity and accounts for differing levels of team identification to assess the reputational threat to a university sport program following a crisis. Using a 2x2x2 experimental design, research was conducted with university students to evaluate their responses to a crisis involving members of a university basketball program. The results indicate that an apology may not be needed when corrective action, a related accommodative crisis response, is used. Crisis severity was found to impact team supportive behavioral intentions of participants (i.e., they were less likely to support a team when crisis severity increased), and basketball team identification helped predict significant differences among participants related to both the reputational threat to the program and team supportive behavioral intentions. The crisis information was found to have no impact on university donor intentions. The results contribute to a small number of research studies that have shown apologies may not always be necessary, at least with this student group of participants, even under circumstances when SCCT predicts an apology to be the most effective crisis response strategy. The practical implications of this are useful for public relations practitioners helping to determine organizational responses to crises. In addition, the inclusion of audience identification as an independent variable was important. Significant differences were found between the high and low identification students, indicating that including the variable could improve crisis managers’ anticipation of this audience’s responses. ACKNOWLEDGEMENTS Completion of this research publication would not have been possible without the support of my dissertation committee. I would like to thank my dissertation advisor Dr. Stephen Lacy for his prompt and well-developed feedback, and my dissertation committee, Dr. Richard Cole, Dr. Charles Atkin, and Dr. Pamela Whitten, for all of their assistance throughout the process. My wife Heather has been incredibly supportive of the time I have put into this project. Our children, Lyla and Elyise, helped to keep it all in perspective. My parents were always interested in my graduate school progression and I wish my father were still here to celebrate its completion. iv TABLE OF CONTENTS LIST OF TABLES......................................................................................................................... vi INTRODUCTION ...........................................................................................................................1 LITERATURE REVIEW ................................................................................................................3 Crisis Communication and Crisis Response Strategies .......................................................3 Sports Public Relations (Sports Information) ....................................................................10 Media Relations in Sports Information..............................................................................13 Sports Marketing/Fan Identification ..................................................................................15 Summary and Research Questions/Hypotheses.................................................................18 METHOD ......................................................................................................................................22 Design and Stimulus Materials ..........................................................................................22 Participants.........................................................................................................................23 Procedures..........................................................................................................................25 Measures ............................................................................................................................25 Pretest.................................................................................................................................28 RESULTS ......................................................................................................................................29 Factor Analysis ..................................................................................................................29 Scale Reliabilities...............................................................................................................31 Manipulation Checks .........................................................................................................31 Study Results .....................................................................................................................34 Post Hoc Analysis ..............................................................................................................40 Post Hoc Analysis of Basketball Behavioral Intention Measures .....................................41 DISCUSSION ................................................................................................................................42 Limitations .........................................................................................................................46 Future Research .................................................................................................................47 APPENDICES Appendix A........................................................................................................................50 Appendix B ........................................................................................................................53 REFERENCES ..............................................................................................................................60 v LIST OF TABLES TABLE 1 Rotated Factor Matrix For Dependent Measures and Identification Variable...................30 TABLE 2 Manipulation Checks .........................................................................................................33 TABLE 3 MANCOVA Results for Main Effects for Crisis Response (Apology), Crisis Severity, and Identification......................................................................................34 TABLE 4 Results for Follow-up Univariate ANOVAS for Crisis Response (Apology), Crisis Severity, and Identification......................................................................................37 TABLE 5 Mean Scores of Dependent Variables As A Result of Experimental Condition ...............37 TABLE 6 MANOVA Results for Model Significance for Basketball Behavioral Intention Items ...................................................................................................................42 vi Introduction Research in the public relations field about crisis communication and management is extensive (for a recent review, see Avery, Lariscy, Kim, & Hocke, 2010). The result has been a much better understanding of how crisis managers should respond when their organization is impacted by a crisis. Key target audiences are known to react differently depending on the crisis type and an organization’s crisis responses. However, while researchers have investigated both actual and fictional crises dealing with a wide variety of business organizations (e.g., oil companies, restaurants, drug companies), far less attention has been devoted to crisis communication involving university sports. The amount of media coverage devoted to university sports, particularly football and basketball, is extraordinary and, at the same time, Burton and Howard (2000) explain the high likelihood of a crisis affecting a sport organization as “only a matter of time before an unexpected ‘bombshell’ is dropped” (p. 44). Football programs alone include rosters of 100 or more players (Sokolove, 2002), and the total number of athletes at National Collegiate Athletic Association (NCAA) member institutions in the United States is over 360,000. Not surprisingly, a recent study of NCAA Division I athletic programs found that 70% had experienced some type of crisis during the previous year (Hessert, 1998). When a crisis happens involving or impacting a university team, the media coverage can quickly extend beyond local media to become national news. Even worse, from the perspective of a university public relations practitioner, it’s not surprising for a sports crisis to go beyond the sports section to earn front-page news status (PR Week, 2007). Under the circumstances, when a crisis can impact both sports and non-sports fan with university ties, an improved understanding of appropriate crisis responses that will minimize reputational damage is important. 1 Successful athletic programs help generate revenue through merchandise and ticket sales and media packages (Fulks, 2002). Programs have also been shown to increase student applications and alumni contributions (Grimes & Chressanthis, 1994; Toma & Cross, 1998). The influence of sports on universities is enough that a number of schools have recently tried to develop athletic programs as a way to improve the university’s brand identity (Judson & Carpenter, 2005). When a crisis involves a university athletic department or one of its teams the media interactions are typically coordinated by the sports public relations practitioners, also called sports information directors (SIDs). As a result of their media relationships, the SIDs are used by athletic directors and coaches to facilitate communication with the media and are often the first people contacted by media members developing stories. This places SIDs in a unique position. They have opportunities to advise athletic directors and coaches on strategic responses to crises. However, due to a lack of research on sports-related crises at universities, their decisions and recommendations are typically based on past experience or intuition. Their ability to choose appropriate response strategies based on an understanding of target audience reactions needs to be improved. An appropriate approach to studying crisis response strategies is to use Situational Crisis Communication Theory (SCCT), which categorizes the responses and recommends situations when each should be used (Coombs, 1995, 1998, 2007). Similar to an approach used by Coombs and Schmidt (2000), this research project examines the actual strategies used in a crisis situation and evaluates their effectiveness with a relevant target audience. A review of crisis communication, sports public relations, and sports marketing research contributes to the 2 development of the research questions and hypothesis by considering the moderating effect of fan identification on their reactions. An experimental design is used to test these ideas. Literature Review Crisis Communication and Crisis Response Strategies Crisis communication issues have attracted increasing amounts of attention from public relations scholars (for a recent review, see Avery et al., 2010). Crises have the potential to threaten an organization’s reputation, and appropriate organizational responses may mitigate the effects on key target audiences (Coombs, 1995; Coombs, 2007). From a public relations perspective, a crisis has been defined in a variety of ways. Coombs (1999) described a crisis as “an event that is an unpredictable, major threat that can have a negative effect on the organization, industry, or stakeholders if handled improperly” (p. 2). Sellnow, Ulmer, and Snider (1998) call a crisis an unexpected, nonroutine event that creates uncertainty and threatens an organization’s priority goals. Holtzhausen and Roberts (2009) simply state that a crisis is an unplanned event that could potentially damage an organization’s image; consequently, this requires choices among response strategies. Consistent among the definitions is consideration for the unplanned nature of a crisis and its potential to negatively impact organizational success. Due to the high level of media attention devoted to sports, the most appropriate definition is provided by Fink (1986) who considers a crisis: A situation that runs the risk of escalating in intensity, falling under close media or government scrutiny, interfering with the normal operations of business, jeopardizing the positive image presently enjoyed by a company or its officers, and damaging a company’s bottom line in any way. (p. 15-16) 3 A crisis that hurts an organization’s reputation (image) can result in financial losses and, if it’s severe enough, threaten the long-term survival of an organization (Coombs & Holladay, 1996). In a university setting, a sports crisis is unlikely to threaten the long-term survival of the university, but it can result in the firings of coaches or administrators, suspensions of athletes, or the removal of athletes from university teams. All instances have the potential to reduce the revenue-generating ability of the athletic program. Early research into crisis response strategies focused on how organizations could protect their reputations from public attack using apologia (Ware & Linkugel, 1973). However, recognition that organizations were using additional strategies resulted in the development of Coombs’ (1995, 1998, 2007) Situational Crisis Communication Theory (SCCT). According to SCCT, a crisis manager who understands a crisis situation “can determine which crisis response strategy or strategies will maximize reputational protection” (Coombs, 2007, p. 166). When an organization is responsible for a crisis (i.e., members of an organization knowingly engaged in actions that caused or contributed to a crisis), the risk of it having a negative impact on the organization increases and crisis response strategies should be more accommodative (Coombs & Holladay, 1996; Coombs & Schmidt, 2000). If an organization is not responsible for a crisis (e.g., natural disasters, accidents, rumors), crisis response strategies should be more defensive. Coombs (1998) grouped crisis response strategies into seven categories that could be placed on a continuum ranging from defensive to accommodative. The categories include denial, evade responsibility, excuse, justification, ingratiation, corrective action, and mortification. Denial can be denying that the event occurred or that the accused performed it. Evading responsibility includes shifting the blame, pointing out a lack of control over the event’s 4 occurrence, or justifying actions based on good intentions. Excuse admits a crisis exists but minimizes organizational responsibility. Justification admits a crisis but downplays its severity. Ingratiation reminds people of past or present good works as a way to offset negative associations with the crisis. Corrective action attempts to repair the crisis damage, prevent a repeat of the crisis, or both. Mortification is accepting responsibility and apologizing. Corrective action and mortification are the two most accommodative strategies. Although Coombs (1998) references research that distinguishes between defensive and accommodative strategies (Marcus & Goodman, 1991), he does not explicitly define which strategies are placed into each category. The following comment helps to provide some clarity, “Accommodative strategies accept responsibility, take remedial action, or both, whereas defensive strategies claim there is no problem or try to deny responsibility for the crisis” (Coombs, 1998, p. 179-180). This identifies corrective action and mortification as accommodative strategies and denial, evade responsibility, and excuse as defensive strategies. Justification and ingratiation remain in the middle of the continuum without a clear fit either category based on the information provided. Different strategies are recommended for an organization depending on the type of crisis it is facing and researchers have argued that similar crises can be managed by using similar responses (Pearson & Mitroff, 1993). A variety of typologies exist and in earlier SCCT articles the crises have been categorized in different ways. For example, Coombs (1995) used internalexternal and intentional-unintentional dimensions to help categorize four different types of crises labeled faux pas (external and unintentional), terrorism (external and intentional), accidents (internal and unintentional), and transgressions (internal and intentional). Later Coombs and Holladay (2002) reduced 13 crisis types into three different clusters: victim, accidental, and 5 preventable. The simplified version has endured and Coombs (2007) recently described the clusters this way: • Victim cluster: The organization is also a victim of the crisis; Weak attributions of crisis responsibility produce a mild reputational threat; Examples include natural disasters, rumors, workplace violence, and product tampering. • Accidental cluster: Unintentional organizational actions lead to the crisis; Minimal attributions of crisis responsibility produce a moderate reputational threat; Examples include stakeholder claims of inappropriate organizational actions, technical-error accidents, and technical-error product harm. • Preventable cluster: The organization knowingly placed people at risk, engaged in inappropriate actions, or violated laws or regulations; Strong attributions of crisis responsibility produce a severe reputational threat; Examples include human-error accidents, human-error product harm, organizational misdeeds with no injuries, organizational misdeeds with injuries, and organizational misdeed management misconduct. Much of the SCCT research has focused on crises that fall under the preventable cluster due to the potential for strong negative reactions of target audiences that can impact an organization’s future success (Claeys, Cauberghe, & Vyncke, 2010; Fediuk, Coombs, & Botero, 2010). Research results have confirmed the effectiveness of defensive strategies when an organization is not responsible and accommodative strategies when an organization is responsible for a crisis (Coombs & Holladay, 1996; Coombs & Holladay, 2008; Coombs & Schmidt, 2000; Dean, 2004). However, early theoretical descriptions of SCCT do not clarify differences between related strategies (Coombs, 1995, 1998). Presumably an organization that is 6 responsible for a crisis should move to the accommodative end of the continuum and use mortification. What is not clear are the circumstances under which a related accommodative strategy be sufficient to minimize the reputational threat. Fortunately, some recent research has begun to compare and explore differences in audience reactions to related crisis response strategies. For example, instead of comparing denial to apology, two dramatically different strategies, Coombs and Holladay (2008) compared apology to additional accommodative, and hence more equivalent, strategies such as expressing concern (a sympathy response) and compensating those affected by the crisis. Results show that “sympathy and compensation can be just as effective (as apology) in producing a favorable reaction from stakeholders” (Coombs & Holladay, 2008, p. 255). A review of the experimental manipulations used in the study, however, raises some concerns. The apology condition was developing using a quote from a company spokesperson. The quote indicates that the company accepts responsibility and that it hopes those affected by the incident can provide forgiveness. An actual apology (e.g., “We’re sorry”; “We apologize”) is not included. When the manipulation check was conducted, the results only state that the apology condition was significantly different from the information only condition. It’s not clear if differences existed between the apology and other related response strategies (sympathy and compensation). If there are not significant differences in the perceptions of the strategies, the interpretation of the results may not be accurate. Such a finding is important for crisis managers because, if true, it may indicate that it’s not always necessary to issue an apology – something that can be an expensive financially for an organization (Fucs-Burnett, 2002; Patel & Reinsch, 2003; Tyler, 1997) – when other related accommodative strategies are acceptable. A stronger apology manipulation should be developed and evaluated against related strategies. 7 The types of comparisons initiated by Coombs and Holladay (2008) should continue to be further developed. If related strategies are found to be equally effective, then the continuum conceptualization of crisis response strategies is not appropriate since it implies that some strategies are more effective than others when it may in fact not be the case. Researchers using SCCT have also begun to explore how organizations use multiple crisis response strategies to deal with the same type of crisis (Claeys et al., 2010; Coombs, 2007; Coombs & Schmidt, 2000; Vlad, Sallot, & Reber, 2006). Realistically, organizations may use more than a single response strategy when responding to a crisis, and understanding the value of different combinations will contribute to the practical value of SCCT. Coombs and Holladay (2008) discuss how “understanding the effects of different crisis response strategies utilized in the same crisis” is a potential growth area that will benefit from additional empirical research. When combining strategies, Vlad et al. (2006) note that argumentative-structural coherence is important (e.g., mixing apologies with corrective action or ingratiation would be acceptable because all are accommodative strategies). While the comparisons of related strategies and combined strategies help contribute to the practical usefulness of SCCT, these differences have not yet been evaluated with varied crisis severity within the same cluster. Early SCCT research by Coombs (1998) established that high and low crisis severity for a crisis in the preventable cluster influenced the amount of image damage (i.e., an organization’s image was viewed more positively in the low crisis condition than in the high crisis condition). However, when Coombs and Holladay (2008) compared related strategies and Coombs and Schmidt (2000) explored how combined strategies, crisis severity was not included as an independent variable. When Claeys et al. (2010) researched multiple crisis response strategies the crises were manipulated by selecting from different crisis 8 clusters, not by manipulating the severity level within the same cluster. In fact, much of the recent experimental research in crisis communication has not used crisis severity within a crisis cluster as an independent variable, overlooking an important component of crisis communication. Instead the focus has either been on response manipulations while holding the crisis scenario constant (e.g., Coombs & Holladay, 2009; Dean, 2004; Pace, Fediuk, & Botero, 2010), or by manipulating the crisis type by cluster while holding the crisis severity constant (e.g., Coombs & Holladay, 2006; McDonald, Sparks, & Glendon, 2010). An important limitation of SCCT that has yet to be adequately addressed is its lack of attention to personal characteristics that may influence target audience responses. Choi and Lin (2008) note that despite an increasing amount of research exploring how organizations strategically choose crisis responses, “little attention has been given to consumer variables (e.g., emotion, involvement) and how those variables can influence the dynamics of SCCT” (p. 18). Indeed, the criticism is accurate as much of the published SCCT research does not address consumer variables (Claeys et al., 2010; Coombs, 2004; Coombs & Holladay, 1996; Coombs & Holladay, 2002; Coombs & Holladay, 2006; Coombs & Schmidt, 2000). The public relations field has long considered how differences among target audiences may influence responses to persuasive messages. Grunig and Hunt (1984) include level of involvement as a key independent variable of the situational theory of publics (audiences), and use it to help explain differences between target publics in what has become a standard inclusion in introductory public relations textbooks. Some progress has been made that considers the impact of emotion, typically anger, in SCCT research (e.g., Coombs & Holladay, 2008; Coombs & Holladay, 2011; Fediuk et al., 2010), but it is only being considered as a dependent variable. 9 Involvement and other similar variables remain understudied despite their potential to improving the understanding of differential audience reactions. Sports Public Relations (Sports Information) Sports public relations is the application of public relations strategies and tactics designed to influence the attitudes and behavior of target audiences in a sport environment. It has been defined as “a managerial communication-based function designed to identify a sport organization’s key publics, evaluate its relationships with those publics, and foster desirable relationships between the sport organization and those publics” (Stoldt, Dittmore, & Branvold, 2006, p. 2). The definition’s important elements – a managerial communication-based function and a focus on relationships with key publics – are consistent with emphasis areas in contemporary definitions of public relations (Wilcox & Cameron, 2009). The practitioners working in sports public relations operate under a variety of titles in professional sports (e.g., communication, marketing, media relations, public relations), but at a collegiate level the most commonly used term to describe their work is sports information. At small universities a single practitioner usually serves as the sports information director (SID). At large universities a sports information department is often created within the athletic department. Regardless of a university’s size, sports information practitioners typically report to the athletic director, the individual responsible for managing the entire athletic department within a university. Overall, the research devoted to sports public relations/sports information is limited but appears to be increasing. The updated Sage Handbook of Public Relations includes a chapter on sports public relations (Isaacson, 2010) after the 2001 edition included a chapter focused specifically on collegiate sports information (Neupauer, 2001). Scholars in public relations and 10 related disciplines have completed a number of studies using a diverse set of research methods that contribute to the overall understanding of this specialized part of public relations practice (e.g., Desmarais & Bruce, 2008; Fortunato, 2000; Funk & Pritchard, 2006; Hardin & McClung, 2002; L’Etang, 2006; McCleneghan, 1995; Neupauer, 1999; Stoldt, Miller, & Comfort, 2001; Woo, An, & Cho, 2008). Desmarais and Bruce (2008) explored how sports announcers use stereotypes when describing international rugby matches. Hardin and McClung (2002) surveyed sports information directors to gather demographic information about practitioners working in the field. Neupauer (1999) used purposive sampling to explore the possibility of trait differences between sports information practitioners employed at small and large academic institutions. However, while the aforementioned studies contribute to the knowledge base in sports public relations, key issues that may improve target audience relationships and impact athletic department revenue generation or prevent revenue loss remain uninvestigated. Stoldt et al. (2001) surveyed athletic directors at NCAA Division I, II, and III institutions to gain an understanding of their perceptions of the work done by sport information directors. Results showed that a majority of the SIDs (92.3%) are perceived to primarily fill technical roles. The athletic directors’ highest level of confidence in sports information staff’s ability to perform public relations tasks were on producing sports information materials (e.g., media game notes, game programs, media guides), working with coaches and athletes, maintaining media contacts, and coordinating special events. Conversely, the lowest levels of confidence were for conducting public relations research, mediating conflicts, setting public relations goals, and identifying emerging issues. 11 When athletic directors were asked to identify the benefits they received from public relations programs, those cited least frequently included a variety of ways to increase revenue generation (e.g., ticket and merchandise sales). In response to items asking about strong and weak departmental relationships, the weakest perceived relationships were with students, alumni, and boosters. Stoldt et al. (2001) summarized their results by stating, “If SIDs are indeed their athletic departments’ top public relations officers, and yet serve in limited public relations capacities, then it seems likely that college athletic departments are failing to maximize their public relations effectiveness” (p. 170). Similar to the criticisms of earlier crisis communication research (Dean, 2004; Coombs & Holladay, 2008; Coombs & Schmidt, 2000), few of the published research articles on sports information and sports public relations provide evidence-based research results that can help practitioners improve their public relations effectiveness. Many of the articles include descriptive results about the nature of daily responsibilities and provide a demographic profile of sports public relations practitioners (e.g., Harden & McClung, 2002), or are developed based on case studies of single sport organizations (e.g., Jensen & Butler, 2007). Certainly this approach helps to inform practitioners and educators in the field, but it rarely provides results that can be applied by practitioners or taught by educators to address the issues raised by Stoldt et al. (2001) (i.e., impact on revenue generation and improved organizational relationships). One exception is Funk and Pritchard’s (2006) article exploring the effects of positive and negative newspaper coverage on attitudes towards professional sport teams. Using a repeated measures pre-post design, they found that commitment influences a reader’s processing of messages and, as a result, can moderate reader responses. Committed readers had better recall of supportive articles and less committed readers recalled more facts from negative articles. 12 According to the authors, the study “emphasizes how important media relations are for altering consumer beliefs and feelings about organizations” (p. 618). In addition, practitioners should consider what type of responses can be expected depending on the commitment level of the target public and the valence of recently published news stories about the organization. Media Relations in Sports Information Media relations in public relations practice has been defined as “working with mass media in seeking publicity or responding to their interests in the organization” (Wilcox & Cameron, 2009, p. 10). The value of engaging in media relations is to capitalize on the thirdparty credibility associated with a message published or broadcast by a member of an independent media organization (Sweetser, Porter, Chung, & Kim, 2008). Its use as a tactic by public relations practitioners is widespread and prevalent; however, in sports public relations it may be even more popular. Stoldt et al. (2006) describe media relations as the most commonly used tactic by sports public relations practitioners. Their application of the tactic often involves tasks intended to facilitate media coverage of sporting events. These tasks include managing press credentials, organizing and managing a press area (e.g., press box, post-game interview room), designing and writing extensive media guides, writing news releases, and researching and writing game notes. Typical results of this attention to the media include consistent coverage of sporting events, the development of game stories summarizing the outcome, and news stories focused on events within the game or about its participants. In a crisis situation media relations remains important, albeit from a different perspective. Instead of working with the media to generate publicity, sports information practitioners will be addressing media requests for information and interviews, the second half of Wilcox and 13 Cameron’s (2009) definition of media relations. In fact, the media are often the most important external public for an athletic department to communicate with in a crisis because of their access to other external critical publics and to immediately publish or broadcast information (Stoldt et al., 2006). Sports public relations practitioners often recognize the newsworthiness of a crisis and are willing to work with the media to facilitate coverage. In a 2008 interview, the director of public relations for a Major League Baseball team in the Midwest, commented on the interaction with media members covering a negative news story by saying, “We understand that they are just doing their job. We had one player suspended (for steroid use) and some negative stories were written. We held a mini-press conference with him in which he explained his side, served the suspension and it was over with.” (personal communication, April 20, 2008). Similarly, Stoldt et al. (2001) advocate that sports public relations practitioners work with the media in a responsive and accommodating way and even suggest positioning the organization as the best source of information for the media in a crisis situation. However, once the crisis has happened and the resulting media reports have been published or broadcast, little is known about the impact the news will have on target audiences and more research is required before evidence-based recommendations can be provided to practitioners (Isaacson, 2010). Of particular importance to a university’s athletic department are the future behavioral intentions of its fans. Will the crisis and resulting media coverage affect their support of the university’s athletic programs? Decreased support could take the form of attending, watching, or listening to fewer games; purchasing less merchandise; or donating less money to the university. 14 Because it is not reasonable to expect all fans to respond the same way to a crisis, the next section reviews sports marketing and fan identification research that help provide ways to segment an audience. Appropriate audience segmentation will enable evaluation of differential behavioral intentions that result following a crisis involving a university sports team. This can help sports public relations practitioners determine appropriate organizational responses and minimize the financial losses that could result from the crisis. Sports Marketing/Fan Identification Fan behavior has been explored from a variety of perspectives that have implications for sports public relations practitioners. With a consistent focus on understanding methods of improving attendance and developing a fan base, multiple studies have focused on on-field success (Wann, Dolan, McGeorge, & Allison, 1994; Wann, Tucker, Schrader, 1996; Whitney, 1988; Zhang et al., 1997). Researchers have also evaluated the impact of a variety of other pertinent factors, including family members (James, 1997; Kolbe & James, 2000), new stadium development (Coffin, 1995; Rivers & DeSchriver, 2002), median household income (Noll, 1974), roster turnover (Kahane & Scmanske, 1997), and star players (Rivers & DeSchriver, 2002). Recent sports fan research has focused on fan identification levels as a way to understand how teams can develop an extensive and loyal fan base (Judson & Carpenter, 2005; Kwon & Trail, 2001; Wann, Brewer, & Royalty, 1999; Wann & Dolan, 1994). Identification has been defined as the spectators’ perceived connectedness to a team and the experience of the team’s failings and achievements as one’s own (Ashforth & Mael, 1989). Logically then, as perceived connectedness increases, the support an individual has for the group will increase as well 15 (Bhattacharya, Rao, & Glynn, 1995; Dietz-Uhler & Murrell, 1999; Fisher & Wakefield, 1998; Madrigal, 2001). Madrigal (2001) found that sports fans that identified strongly with teams showed greater purchase intentions for the sponsored company’s product than did those who had weak team identification. Similarly, Dietz-Uhler and Murrell (1999) found that those with a strong university identity evaluated their university football team more favorably over the course of the season, whereas those with a weak university identity evaluated the team about the same regardless of game outcomes (wins or losses). It is worth noting that in a university sports setting, even the fans with low identification are important. Despite their low identification, it is still possible that students in this group engage in behaviors that benefit a university sports team. Although it happens with less frequency, these students are still likely to occasionally watch games and purchase merchandise. Previous research has shown that much higher percentages of college students indicate having at least some interest in major sports at their university than the numbers in the general public (Taylor Research, 1998). Sports fan identification research calls these individuals “social fans” who enjoy the entertainment level of a sport without caring about the outcome of games; instead, it is the social interactions they may have at a game that are valued (Sutton, McDonald, Milne, & Cimperman, 1997). Social identity theory provides an appropriate and effective way of understanding fan identification (Gwinner & Swanson, 2003). Social Identity Theory. Social Identity Theory attempts to capture how an individual’s identity group memberships form his or her perspectives and experiences in different settings. According to the theory, identity consists of both personal and social components. The personal identity stems from idiosyncratic characteristics, such as personality and physical and intellectual 16 traits. Social identity, in contrast, derives from salient group memberships such as sex, race, class, and nationality (Ashforth & Mael, 1989); and involves the processes of self-categorization and attachment to salient group classifications and particular social categories (Pettigrew, 1986). From this perspective, social identity is defined as “an individual’s knowledge of his or her memberships in social groups together with the emotional significance of that knowledge” (Tajfel, 1978, p. 63). An important part of social identity in the context of sports fandom is that the identification people have with a team allows them to partake vicariously in accomplishments beyond their own powers (Katz & Kahn, 1966). Cialdini et al. (1976) called this basking in reflective glory (BIRG) and found support for the phenomenon in experimental tests that “showed a significant tendency for students to strive to associate themselves publicly with their university’s football team more after the team had been successful” (p. 374). Stated another way, the successes or failures of a sports team in athletic contests will affect the personal team-brand images of fans through their social identification connections with the team. Social identity only acquires meanings by social comparison with other groups due to its evaluative feature. It assumes that individuals tend to maintain positive social identities by engaging in social comparisons that distinguish between in-groups and out-groups (Tajfel & Turner, 1979). This means that a successful sports team provides positive social identities for fans when they compare themselves to the fans of other teams. By being connected to a successful group, the fans’ social identities are positive (Fischer & Wakefield, 1998). Social Identity Theory provides a way to understand existing differences and differential responses among members of a target audience. That is, fans with high levels of identification 17 with a team are likely to respond differently than fans with low levels of identification following a crisis. Summary and Research Questions/Hypotheses As it was described in the preceding sections, students are one of the key target audiences for university sports and their team-supportive behaviors are important to sports public relations practitioners, athletic directors, and athletic departments (Stoldt et al., 2001). Evaluating their responses to a crisis can assist with the development of appropriate organizational responses. The following research questions and hypotheses are developed for evaluation with this target audience. According to SCCT, when an organization is responsible for a crisis (i.e., organizational actions caused it), it should use accommodative responses. Coombs (2007) identifies crises of this type as preventable. However, one of the problems with SCCT’s ability to make predictions is that it does not distinguish between which accommodative strategies are needed to minimize reputational threat. A logical assumption is that when an organization is responsible it should use the most accommodative response, apology. However, apologies can be expensive for an organization (Fucs-Burnett, 2002; Patel & Reinsch, 2003; Tyler, 1997), and may make it legally liable for damages. From an organizational perspective, it may be beneficial if it does not have to issue an apology. Coombs and Holladay (2008) recently compared apology to other accommodative strategies as responses to a preventable crisis and found that it might not be necessary to go to the end of the accommodative continuum; results show that expressing concern as a form of sympathy and compensating those affected by the crisis, can be as effective as an apology. 18 When preventable crises happen involving university athletic departments a common response is to use the accommodative strategy of corrective action, typically in the form of suspensions. The length of the suspension varies based on the severity of the violation and an individual’s prior history of problems. The suspension serves two purposes: one, to discourage the individual from engaging in similar behavior in the future; and two, to appease the stakeholders who support the organization. The stakeholders have often not been directly impacted by the crisis, but they remain interested in what happened and how the university’s athletic department responds. This is not unusual in crisis communication. Coombs and Holladay (2008) describe how “the vast majority of the targets for public crisis response strategies are stakeholders who are not victims of the crisis” (p. 255). SCCT does not currently address if corrective action is enough or if it needs to be accompanied by an apology in an organization’s crisis response to a preventable crisis. This leads to the following research question: RQ1: Is it necessary to use the most accommodative crisis response strategy (an apology), or is a related accommodative response (corrective action) enough to minimize the reputational threat of a preventable crisis? The relationship between crisis severity and an organization’s reputational threat is an important component of SCCT. Coombs (2004) considers it to be an intensifier (i.e., the reputation threat increases as severity increases), and early SCCT research confirmed the relationship (Coombs, 1998). Related crisis communication research found that a less severe crisis improved the target audience’s behavioral intentions related to product purchases (Arpan & Roskos-Ewoldsen, 2005). This leads to the following hypothesis: H1: An increase in crisis severity will produce a greater reputational threat for a university sport program. 19 When SCCT is applied to sport organizations an important variable – fan identification – needs to be accounted for because of its potential influence on target audiences. This limitation of the theory has been recognized by other researchers in the public relations field. Choi and Lin (2008) emphasized the need for consideration of consumer variables, due to the potential for these variables to influence SCCT outcomes. One recent study by McDonald et al. (2010) confirmed the role of involvement in understanding target audience reactions. As it was described earlier, the sports marketing research has focused on identification as a way to understand fans’ attitudes and behavioral intentions. SCCT in its current form does not account for these varied reactions. It predicts that when more crisis responsibility is attributed to an organization (e.g., a preventable crisis), the organization’s reputation among target audiences will be damaged (Coombs, 2007; Coombs & Holladay, 1996, 2001). However, prior research on sport fan identification has shown that fans have different responses that can impact both attitudes (Dietz-Uhler & Murrell, 1999) and behavioral intentions (Madrigal, 2001). Social Identity Theory can be used to improve the predictive value of SCCT when considering sport fans’ reactions to a crisis and a sport organization’s crisis response strategies. Students who have high team identification benefit from the “basking in reflective glory” effect, something that has a positive effect on their esteem (Cialdini et al., 1976). Because they value being a part of the group and the team’s success gives them a positive social identity when compared to other fans (Fischer & Wakefield, 1998; Tajfel & Turner, 1979), it is logical to expect that the crisis will not have as strong of an impact on their attitudes and behavioral intentions as it would for students with low identification. This is consistent with Funk and Pritchard’s (2006) research that found more committed sports fans had a tendency to overlook negative information about their sports team. This contradicts the simple prediction of SCCT that 20 when an organization is responsible for a crisis, it will have a negative impact on its reputation. Instead members of a target audience are expected to react differently to the “negative” information about the crisis itself, based on their level of identification with the sport organization. These differential reactions can be evaluated by examining attitudes and behavioral intentions, both of which should be affected by a crisis (Fediuk, Coombs, & Botero, 2010; Coombs, 2007). This is consistent with a recent recommendation that crisis response research needs to include dependent variables that reflect target audiences’ behavior (e.g., supportive behavior and purchase intentions) (Fediuk, Pace, & Botero, 2010). This leads to the following hypotheses: H2: The crisis information will have a greater negative impact on a university sport program’s reputation among low identification students than high identification students. H3: The crisis information will have a greater negative impact on supportive behavioral intentions for a university sport program among low identification students than high identification students. The impact of a crisis involving a university sport program on the university overall is not clear. Successful programs can help generate revenue for universities (Fulks, 2002), and in some instances have increased student applications and alumni contributions (Grimes & Chressanthis, 1994; Toma & Cross, 1998). Certainly then, the ramifications of negative information should also be evaluated. The extensive amount of media coverage devoted to university sports means that both minor and major crises are likely to be covered by the news media, exposing a high number of university stakeholders to the incidents and the university’s public relations responses. It is not known if the crisis information about a university sport 21 program will also influence any university behavioral intentions or the university’s overall reputation. One behavior of particular interest to universities is donor behavior. If a crisis involving a sport program also impacted university donor behavior, the implications would be serious. As a result, the following research questions are posed: RQ2: What impact will the crisis information have on university donor intentions of low identification students compared to high identification students? RQ3: What impact will the crisis information have on the university’s reputation among low identification students compared to high identification students? Method Design and stimulus materials To test the research questions and hypotheses, a 2 (response strategy: corrective action and corrective action with apology) x 2 (high and low crisis severity) x 2 (level of group identification: high and low) between-subjects experimental design was used. Fictional crises scenarios were developed based on actual crises involving NCAA Division I university student athletes. Information about the crises, criminal charges, police procedures, and typical university athletic department responses from published media reports about the incidents was used to help increase the believability of the scenarios. The two high crisis severity scenarios involved felony burglary charges against four university basketball players, and included the value of the stolen items ($15,000), the types of stolen items (laptop computers, TVs, iPods, and DVD players), and a description of how the crimes occurred (dorm rooms in a university residence hall). The low severity conditions involved the same number of players and description of how the crimes occurred, but lowered 22 the burglary charges to misdemeanors and decreased the types of stolen items to only include TVs and iPods. The apology manipulation was developed using three different apology references: an apology headline, an apology reference in the story lead, and a short apology quote. The explicit apology inclusions are designed to strengthen the apology manipulation in an effort to better evaluate its effectiveness when used with a related accommodative strategy, corrective action. This should help overcome a limitation of earlier research by Coombs and Holladay (2008) that also compared an apology to related accommodative strategies. All four scenarios were approximately equal in length and the remainder of the content was consistent across scenarios. The entire scenarios are included in Appendix A. To increase the believability of the scenarios, actual crisis response strategies used by university basketball programs were included. The program’s responses were appropriate based on recommendations by SCCT. That is, members of the basketball team were responsible for the crisis and, consequently, the program engaged in two different accommodative responses. The text of the scenarios is included in a separate questionnaire. The decision to focus on basketball was made due to the prominence and revenuegenerating ability of the sport at the university where the research was conducted. The prominence, combined with the high student attendance at games, increased the likelihood that many of the students participating in the study had previously attended games. In addition, the large size of the student population at the university still allowed for variance in group identification levels of participants. Participants 23 A power analysis was conducted to determine the number of participants for the experiment. An acceptable level of power is .80 (Keppel, 1991; Warner, 2008). To understand 2 the expected population effect size for this type of research, the reported effect sizes (η ) in comparable research were examined. In general, the effect sizes are between .09 and .13 (Coombs, 2004; Coombs & Holladay, 2008; Coombs & Schmidt, 2000). By using the statistical power tables developed by Jaccard and Becker (1997) – presuming alpha = .05, power = .80, and the approximate population eta squared is .10 – 36 participants were needed in each cell. With eight different cells in the experiment, the minimum number of participants was 288. Participants were 296 undergraduate students at an NCAA Division I Midwestern university with a prominent, revenue-generating men’s basketball program. The ages of participants ranged from 18 to 27 years old (M = 19.88, SD = 1.3). Women (59.8%, 177) outnumbered men (40.2%, 119) and most of the participants were White/Caucasian (83.1%, 246), followed by Black/African American (8.1%, 24), Hispanic (4.4%, 13), Asian/Pacific Islander (2.7%, 8), and Other/Mixed Race (1.7%, 5). Compared to demographic information of all undergraduate students attending the university (“Michigan State University College Portrait,” 2010), female (52%) and White/Caucasian (73%) students were overrepresented by about 8% and 10% respectively. Black/African American (7%) and Hispanic (3%) students were slightly overrepresented. The average age of participants was close to the overall undergraduate average (20). Male (48%) students were underrepresented by about 8% and Asian/Pacific Islander (4%) students were slightly underrepresented. 24 Students were recruited through university courses and offered a chance to win an iPod Nano in exchange for their participation. Three iPod 8GB Nanos were given away, one each in three different large lecture courses. Procedures The research was conducted in a classroom setting. The researcher informed students that their answers would be kept confidential, they could decline to answer any of the questions, and they should carefully read the materials and respond to the following questions. Participants received paper copies of a consent form, one of the four crisis scenarios, and the response items. Reading and responding to the items took approximately 15-20 minutes. The different scenarios were randomly ordered by the researcher before distributing them to participants. Measures To conduct data analyses, the scores of multiple items were added to obtain an index score for each dependent variable. Factor analysis was conducted to verify the effectiveness of the items in measuring the variables. Cronbach’s alpha was used to assess the reliability of the scales. Reputational threat. Reputational threat was operationalized by adapting organizational reputation items used by Coombs and Holladay (1996), and by developing new items specific to threats for a university and a university sport program. The items, using seven-point Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree), are: 1. The basketball program represented in this scenario is taking responsibility for its actions. 2. Students at the university represented in this scenario should be proud of the basketball program’s reaction to this crisis. 3. The problem in this scenario occurs in most college basketball programs. 25 4. The basketball program’s reaction will be viewed positively by the general public. 5. The incident that occurred will affect the university’s reputation among the general public. 6. Graduates of this university will be satisfied with the way the basketball program handled this crisis. The items were adapted slightly by replacing “basketball program” with “University” to evaluate the impact of the reputation threat to the university overall. Behavioral Intentions. Four seven-point Likert scale items were created to measure behavioral intentions relevant to a sport organization. Items dealt with game attendance, game viewing, purchase of team merchandise, and future donor behavioral intentions. These topics were chosen because of the impact that an increase or decrease in these behaviors by students could have on the financial success of a university athletic department. The items are: 1. If I were a student at this university, this incident would decrease the likelihood that I would attend its basketball games. 2. If I were a student at this university, this incident would decrease the likelihood that I would watch its basketball games on TV. 3. If I were a student at this university, this incident would decrease the likelihood that I would buy team clothing during the next few months. 4. If I were already an alum of this university, this incident would decrease the likelihood that I would donate money to support the basketball team. An additional behavioral intention item, also on a seven-point Likert scale, was created to help differentiate between donor intentions toward the basketball team and the university. The item is: 26 1. If I were already an alum of this university, this incident would decrease the likelihood that I would donate money to support an academic program at the university. Identification. The evaluation of differences among participants with high and low identification toward college basketball were made using group identification items developed by Fischer and Wakefield (1998). The items were adapted to fit this study. The six items use seven-point Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree), and evaluate the degree to which people define themselves in relation to a sports team. Participants were categorized into high versus low group identification using a median split. This was accomplished by adding scores on all items before developing the groups. The items are: 1. It is important to me to maintain strong ties to my university basketball team. 2. Supporting my university basketball team is important to me. 3. One of the things I would tell others about myself is that I am a fan of my university’s basketball team. 4. Being a basketball fan at my university is an important part of who I am. 5. I wear t-shirts, sweatshirts or hoodies that show my support for my university basketball team. 6. I almost think of myself as part of my university’s basketball program. All of the measures used on the questionnaire, along with the item instructions and response options are included in Appendix B. Covariates. Because research involving a sports topic and university basketball team could be influenced by variables not controlled by the experimental design, a number of covariates were measured and included in the analysis. The covariates in this study were gender, high school sports involvement, high school basketball involvement, prior and current basketball 27 student section affiliation, and prior university basketball game attendance. All were measured with dichotomous response options (Yes/No) with the exception of gender (Female/Male). Pretest To evaluate the effectiveness of the experimental manipulations and the measurement of the dependent variables, a pretest was completed with a small sample that had similar characteristics to the target group (Singleton & Straits, 1999). Pretest participants were students at a different NCAA Division I Midwestern university that also has a prominent, revenuegenerating basketball program. After establishing a target goal of 100-200 participants (Dillman, 2007), 132 students successfully completed the pretest. None of these students were part of the main experiment. Results of the pretest confirmed that the experimental manipulations were successful; that is, corrective action was recognized as a crisis response strategy across conditions, and the apology/no apology and high/low crisis severity conditions were significantly different from each other. Factor analysis of the dependent measures was also completed, and results showed that problems existed between the reputational threat items for the basketball program and university. The items were loading on the same factor, indicating that the items were measuring the same variable. In addition, not all of the items fit well with other items on each scale. Two of the reputational items, item 3 (The problem in this scenario occurs in most university basketball programs) and item 5 (The incident that occurred will affect the university’s reputation among the general public) did not load well with the remaining four items on the scale. The behavioral intention item measuring university donor intentions was also included in the factor analysis to ensure it was not a part of the basketball behavioral intention variable. This was confirmed and it did not load well with the behavioral intention items or any of the others. 28 Because the pretest had a small sample size for a factor analysis and it can result in less reliable correlation coefficients (Tabachnick & Fidell, 2001), the factor analysis was repeated with the primary data collection since it had an appropriate sample size for the analysis. Results Factor analysis A factor analysis using a principal axis analysis and varimax rotation was conducted to evaluate the items for the dependent measures and for the identification variable. The first issue that was evaluated, based on the results of the pretest, was the independence of the reputational threat items for the university basketball program and the university. The items loaded together on the same factor (see Table 1), indicating that participants were not separating between the basketball program’s reputational threat and the university’s reputational threat. As a result, the university items were not included in further analysis. The second issue from the pretest that was confirmed was that two of the reputational threat items, item 3 (The problem in this scenario occurs in most university basketball programs) and item 5 (The incident that occurred will affect the university’s reputation among the general public), were not sufficiently related to the other items, nor were they related to the other factors (see Table 1). Consequently, the two items were removed from the scale. The removal resulted in an improvement to the cumulative percentage of variance explained by the remaining items. The remaining four reputational threat items loaded on the same factor with loadings greater than .63, exceeding the .50 cutoff needed to be considered practically significant (Hair, Anderson, Tatham, & Black, 1998). 29 The four basketball behavioral intention items loaded on the same factor with values greater than .56. Examination of the university donation behavioral intention item showed it did not load on the same factor so it was evaluated separately in the data analysis. All six of the basketball identification items loaded on the same factor with loadings greater than .63 and the scale was left unchanged. TABLE 1 Rotated Factor Matrix For Dependent Measures and Identification Variable Factor 1 Factor 2 Factor 3 Item Behavioral Reputation Identification intentions The basketball program represented in this scenario is .657 .064 -.051 taking responsibility for its actions Students at the university represented in this scenario .799 .011 .007 should be proud of the basketball program’s reaction to this crisis The problem in this scenario occurs in most college .124 -.006 .262 basketball programs The basketball program’s reaction will be viewed .704 .026 -.009 positively by the general public The incident that occurred will effect the university’s -.047 .132 .212 reputation among the general public Graduates of this university will be satisfied with the .808 .049 -.054 way the basketball program handled this crisis. The University represented in this scenario is taking responsibility for its actions Students at the university represented in this scenario should be proud of the University’s reaction to this crisis The problem in this scenario occurs at most Universities The University’s reaction will be viewed positively by the general public The incident that occurred will effect the University’s reputation among the general public Graduates of this university will be satisfied with the way the University handled this crisis. .731 -.021 -.021 .857 .050 -.107 .058 -.005 .258 .779 -.032 -.009 .062 .092 .330 .857 .027 .003 If I were a student at this university, this incident would decrease the likelihood that I would attend its basketball games -.118 -.219 .771 30 Table 1 (cont’d) If I were a student at this university, this incident would decrease the likelihood that I would watch its basketball games on TV If I were a student at this university, this incident would decrease the likelihood that I would buy team clothing during the next few months If I were a student at this university, this incident would decrease the likelihood that I would donate money to support the basketball team If I were already a graduate of this university, this incident would decrease the likelihood that I would donate money to support an academic program at the university -.146 -.222 .786 -.106 -.136 .825 -.146 -.116 .599 -.264 -.045 .395 It is important to me to maintain strong ties to MSU’s .096 .832 -.127 basketball team Supporting MSU’s basketball team is important to me .107 .882 -.116 One of the things I would tell others about myself is -.029 .858 -.070 that I am a fan of MSU’s basketball team Being a basketball fan at MSU is an important part of .008 .899 .007 who I am I wear t-shirts, sweatshirts or hoodies that show my -.026 .724 -.078 support for the MSU basketball team I almost think of myself as part of MSU’s basketball .029 .764 .042 program Eigenvalues 5.865 4.537 2.817 Cumulative % of variance explained 23.905 42.211 52.429 Note: Extraction Method was Principal Axis Factoring; Rotation Method was Varimax with Kaiser Normalization. Rotation converged in four iterations. Scale reliabilities The reliability coefficients for all of the dependent measures were well above .70, the generally agreed upon lower limit for the reliability of a scale (Hair et al., 1998). Cronbach’s alpha was .83 for the 4-item reputation threat scale, .86 for the 4-item behavioral intention scale, and .93 for the 6-item team identification scale. Manipulation checks 31 Three items, using a 7-point response scale ranging from 1 (strongly disagree) to 7 (strongly agree), were included on the questionnaire to evaluate the success of the experimental manipulation; do the participants recognize the crisis response strategies being used in the scenario, and is there a recognizable crisis severity difference? Consistent with recommendations by Singleton and Straits (1999), the items were placed immediately after the scenario on the questionnaire, after the manipulation of the independent variables but before the measures of dependent variables. The items were adapted to fit this study based on similar research by Coombs and Schmidt (2000). The items are: • Corrective action – “After the incident described in the scenario, the university’s basketball coach took action intended to prevent future incidents from happening again.” • Apology – “On behalf of the basketball program, the coach apologized for his players’ actions.” • Crisis severity – “The incident described in the scenario is a severe problem for the basketball program.” Because all participants received information about the corrective action taken by the university’s basketball program, the mean of the responses in the different conditions was evaluated to make sure the corrective action response was recognized and that there were no significant differences between the conditions. One-way ANOVAs were used to determine if a significant difference existed between the corrective action only and the corrective action + apology conditions, and the high and low crisis severity conditions. This approach is consistent with previous experimental crisis communication research (e.g., Coombs & Holladay, 2011; Coombs & Holladay, 2009; Coombs & Schmidt, 2000). 32 The corrective action crisis response was appropriately recognized by research participants. The means for each of the four conditions were as follows: high severity-apology condition, M = 5.08, SD = 1.52; high severity-no apology, M = 5.22, SD = 1.50; low severityapology, M = 5.47, SD = 1.35; and low severity-no apology, M = 5.15, SD = 1.50. A one-way ANOVA showed that there were no significant differences between the conditions (F(3, 292) = 1.01, p = .39). The conditions with an apology crisis response (M = 6.28, SD = .88) were significantly different from the conditions with no apology (M = 3.34, SD = 1.66) (F(1, 294) = 361.82, p < .001). In addition, the high severity crisis conditions (M = 5.60, SD = 1.24) were significantly different from the low severity crisis conditions (M = 4.61, SD = 1.31) (F(1, 294) = 44.65, p < .001). Table 2 summarizes the ANOVA results. TABLE 2 Manipulation Checks High Severity Crisis Apology & Corrective Action Manipulation Corrective action Low Severity Crisis Corrective Action Only Apology & Corrective Action M SD M SD M SD M SD 5.08 1.52 5.22 1.50 5.47 1.35 5.15 1.50 Apology & Corrective Action Apology 6.28* 0.88 Corrective Action Only 3.34* High Severity Crisis Crisis severity Corrective Action Only 5.60* 1.66 Low Severity Crisis 1.24 4.61* Note: *p < .001 33 1.31 The manipulation checks confirmed that the experimental manipulations were successful. The corrective action crisis response was consistent across all conditions, and the apology/no apology crisis response and high/low crisis severity conditions were accurately perceived by participants. Study results Data analysis for the research questions and hypotheses was conducted using a MANCOVA, which allowed for one omnibus test for all of the DVs and minimized the Type I error rate. This analysis approach was appropriate because there were three different IVs (crisis response strategy, crisis severity, group identification) and three different DVs (reputational threat, behavioral intentions, university donor intentions), along with six covariates. Although it would be possible to run a series of one-way ANCOVAs, this would result in an inflated risk of a Type I error (Warner, 2008). The covariates included in the analysis were gender, high school sports involvement, high school basketball involvement, prior and current basketball student section affiliation, and prior university basketball game attendance. There were no significant main effects for any of the covariates. Before discussing the main effects for the model, the interaction effects of the independent variables were reviewed. All interaction effects were not significant and, as a result, the remainder of the results and discussion will focus on the main effects. A summary of the main effects of the MANCOVA is provided in Table 3. TABLE 3 MANCOVA Results for Main Effects for Crisis Response (Apology), Crisis Severity, and Identification Source df 34 F p Partial η 2 Table 3 (cont’d) Apology manipulation 3, 272 1.709 .165 .019 Crisis severity manipulation 3, 272 4.112 .007 .043 Team identification 3, 272 6.344 .000 .065 Note: Main effects of MANCOVA model when controlling for Gender, Current Basketball Student Section Affiliation, Prior Basketball Student Section Affiliation, Prior Basketball Game Attendance, High School Basketball Involvement, High School Sports Involvement. All covariates were n.s. RQ1 asked the following question: Is it necessary to use the most accommodative crisis response strategy (an apology), or is a related accommodative response (corrective action) enough to minimize the reputational threat of a preventable crisis? The main effect for apology 2 was not significant (F(3, 272) = 1.71, p = .17, partial η = .019). Although intuitively one would expect that an apology should be used in a circumstance like the one described in the crisis scenario for this study (i.e., members of the organization are responsible for the crisis that has occurred), this result shows that it may not be necessary. When compared to corrective action, one of the most frequently used accommodative tactics by university athletic departments, an apology may not be necessary. This result adds to other recent research that has begun to explore the fine distinctions between related crisis response strategies in an effort to improve the ability of SCCT to make more precise predications. As an example, Coombs and Holladay (2008) compared apology to other accommodative strategies and also found that it might not be necessary to go to the end of the accommodative continuum; results showed that expressing concern as a form of sympathy and compensating those affected by the crisis can be as effective as an apology. However, because there are some concerns about the strength of the apology manipulation used by Coombs and Holladay (2008) (described earlier in this paper), and to 35 determine if dichotomizing team identification into high/low groups influenced the nonsignificant result, a post hoc regression analysis was conducted. The results are described after the main results section under the heading Post hoc analysis and they help to clarify the nonsignificant main effect for apology. H1 made the following prediction: An increase in crisis severity will produce a greater reputational threat for a university sport program. A significant main effect for severity was 2 found (F(3, 272) = 4.11, p < .01, partial η = .043). A follow-up univariate ANOVA indicated that basketball behavioral intentions were significantly influenced by severity of the crisis (F(1, 2 274) = 11.93, p = .001, partial η = .042). A summary of all follow-up univariate ANOVAs is provided in Table 4. Participants in the high severity condition (M = 3.78, SD = 1.46) were more likely to decrease their support of the university basketball program than participants in the low severity condition (M = 3.24, SD = 1.3), as indicated by a change in behavioral intentions (see Table 5). However, follow-up univariate ANOVAs for reputational threat (F(1, 274) = 1.31, p = .25) and university donor intentions (F(1, 274) = 2.07, p = .15) were not significant. This result is somewhat surprising in that the behavioral intention change was expected to be accompanied by differences in the reputational threat. Examination of the means shows that while they are trending in the right direction, M = 4.44 (SD = 1.16) in the high severity condition and M = 4.62 (SD = 1.06) in the low severity condition, the difference is not substantial. This may be indicative of the challenge of manipulating crisis severity. While the manipulation was successful for the experiment, the practical difference was moderate (a difference of .09 on a 7point scale). Perhaps if the severity manipulation can be improved while still maintaining the believability of the less severe crisis, the reputational threat results would be different. These results show that H1 was partially supported. 36 TABLE 4 Results for Follow-up Univariate ANOVAS for Crisis Response (Apology), Crisis Severity, and Identification Source df F p Partial η Apology manipulation Basketball behavioral intentions 1, 274 3.163 .076 .011 University donor intentions 1, 274 0.563 .454 .002 Program reputational threat Crisis severity manipulation Basketball behavioral intentions 1, 274 2.642 .105 .010 1, 274 11.932 .001 .042 University donor intentions 1, 274 2.067 .152 .007 Program reputational threat Team identification manipulation Basketball behavioral intentions 1, 274 1.311 .253 .005 1, 274 14.847 .000 .051 University donor intentions 1, 274 0.973 .325 .004 Program reputational threat 1, 274 5.706 .018 2 .020 TABLE 5 Mean Scores of Dependent Variables As A Result of Experimental Condition High Severity Crisis Low Severity Crisis Apology & Corrective Action Univ. donor intentions Program reputational threat Apology & Corrective Action Corrective Action High Identif. BB behav. intentions Corrective Action Low Identif. High Identif. Low Identif. High Identif. Low Identif. High Identif. Low Identif. 3.54 (1.49 SD) 2.46 (1.82 SD) 4.81 (0.96 SD) 3.93 (1.41 SD) 2.47 (1.72 SD) 4.25 (1.09 SD) 3.46 (1.25 SD) 2.42 (1.42 SD) 4.40 (1.24 SD) 4.19 (1.60 SD) 2.56 (1.54 SD) 4.32 (1.27 SD) 2.76 (1.16 SD) 2.14 (1.31 SD) 5.00 (0.71 SD) 3.40 (1.27 SD) 2.41 (1.61 SD) 4.68 (1.05 SD) 2.78 (1.04 SD) 1.83 (1.11 SD) 4.49 (1.05 SD) 4.00 (1.33 SD) 2.51 (1.73 SD) 4.32 (1.26 SD) Note: All of the DVs were measured on seven-point Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree). For Behavioral Intentions and University Donor Intentions, a lower score indicates that the crisis would not impact a participant’s behavior. For Program Reputational Threat, a higher score indicates a decreased threat. 37 Hypotheses 2-3 and RQ 2 were all related to the impact the crisis information would have on low identification and high identification students. A significant main effect for identification 2 was found (F(3, 272) = 6.34, p < .001, partial η = .065). H2 stated: The crisis information will have a greater negative impact on a university sport program’s reputation among low identification students than high identification students. The follow-up univariate ANOVA indicated that reputational threat for the university basketball program was significantly influenced by student identification with the program (F(1, 274) = 2 5.71, p < .05, partial η = .020). High identification students (M = 4.67, SD = 1.04) had more positive impressions of the basketball program’s response to the crisis than low identification students (M = 4.40, SD = 1.16) (on the 7-point scale, 7 indicated strong agreement with the program’s responsibility, reaction, and satisfaction with handling of the crisis). H2 was supported. H3 predicted the following: The crisis information will have a greater negative impact on supportive behavioral intentions for a university sport program among low identification students than high identification students. The follow-up univariate ANOVA indicated that supportive behavioral intentions toward the university basketball program were significantly 2 influenced by student identification with the program (F(1, 274) = 14.85, p < .001, partial η = .051). High identification students (M = 3.19, SD = 1.31) were less likely to decrease their team support than low identification students (M = 3.82, SD = 1.43) (one the 7-point scale, 1 indicated strong disagreement with changes to team-supportive behavioral intentions). H3 was supported. RQ2 asked the following question: What impact will the crisis information have on university donor intentions of low identification students compared to high identification 38 students? The follow-up univariate ANOVA indicated that university donor intentions toward the university were not significantly influenced by student identification (F(1, 274) = .973, p = 2 .33, partial η = .004). RQ3 asked the following question: What impact will the crisis information have on the university’s reputation among low identification students compared to high identification students? Because the factor analysis showed that the university reputation measurement items loaded on the same factor as the basketball program reputation items, the university reputation items were not included in the analysis. Instead, the significant main effect for identification 2 (F(3, 272) = 6.34, p < .001, partial η = .065) and the results described with H2, indicate that high identification students had more positive impressions of the reaction to the crisis than low identification students. This means that when students identify strongly with the basketball program and the program responds with proper response strategies to a crisis, the university’s reputation will not suffer the same damage that it may with other stakeholder groups. This result is useful for a crisis manager who could then focus more of his or her energy on strategies to minimize reputational damage with the other groups. The partial eta squared results are reported in this study to help provide a second way, in addition to statistical significance tests, of evaluating the results of this experiment. Researchers in social science are increasingly reporting effect sizes to both overcome limitations of statistical significance tests, which can be influenced by sample size, and to improve the ability to compare results across studies. Recent SCCT research has reported partial eta squared effect sizes for significant results that range from .02 to .13 (Coombs & Holladay, 2008; Coombs & Holladay, 2009; Coombs & Schmidt, 2000; McDonald et al., 2010). The partial eta squared results from this study show low to moderate effects, ranging from .02 to .065. 39 Post hoc analysis A multiple regression analysis was conducted for each of the three dependent variables (team supportive behavioral intentions, program reputational threat, and university donor intentions) to evaluate the relative importance of the independent variables (crisis response, crisis severity, and team identification) after controlling for the covariates (gender, current basketball student section affiliation, prior basketball student section affiliation, prior basketball game attendance, high school basketball involvement, and high school sports involvement). With team supportive behavioral intentions as the dependent variable, the overall model 2 was significant (F(9, 278) = 4.443, p < .001), with an R = 0.13. None of the covariates were significant predictors of behavioral intentions. Both crisis severity (β = 2.26, p < .001, pr = .209) and team identification (β = -.16, p < .001, , pr = -.23) were significant predictors, and the apology crisis response manipulation was nearly significant (β = -1.48, p = .05, pr = -.117). The near significance of the apology manipulation produces a different interpretation for RQ1 than the non-significant main effect (p = .17) for apology with the MANCOVA. In addition, the partial correlation coefficient indicates a larger contribution of the apology IV than 2 the small partial eta-squared (partial η = .019) with the MANCOVA. The different results can be explained by the ability to include team identification in the regression analysis without dividing it into two groups. Apparently the group division was suppressing some of the variance of participant responses on the variable and it was enough to hide a near significant result. When program reputational threat was entered as the dependent variable, the overall 2 model was not significant (F(9, 278) = 1.709, p = .087), with an R = 0.05. None of the covariates were significant predictors of program reputational threat. The apology crisis response 40 manipulation (β = 1.18, p = .059, , pr = .113) and team identification (β = .056, p = .086, , pr = .103) were approaching significance, while crisis severity (β = -.62, p = .232, pr = -.072) was not significant. The third regression equation had university donor intentions as the dependent variable. 2 The overall model was not significant (F(9, 278) = 1.808, p = .067), with an R = 0.06. None of the IVs were significant; however, among the covariates, both gender (β = -.39, p < .05, pr = .121) and prior basketball attendance (β = .57, p < .05, pr = .128) were significant. Post hoc analysis of basketball behavioral intention measures My dissertation proposal stated that each of the basketball behavioral intention items would be evaluated separately (i.e., each of the four items was phrased as a separate hypothesis). However, the factor analysis showed that the four items loaded on the same factor so the items were analyzed together as a single dependent variable. The four separate hypotheses were combined to form H3, which stated that the crisis information would have a greater negative impact on supportive behavioral intentions for a university sport program among low identification students than high identification students. As a result of these changes, two different post hoc analyses of the items were conducted. First, a reliability analysis was completed to confirm the items were measuring the same concept. Second, the impact of the IVs on each item was evaluated to determine if the model was significant. The reliability analysis indicated that all four items are measuring the same construct. The correlations in the inter-item correlation matrix were all positive and reasonably large, the corrected item-total correlations were all strongly related to the sum of the other items, and deleting any of the items would not result substantial improvement to Cronbach alpha for the scale (Warner, 2008). 41 Results of a MANOVA showed significant results for each of the behavioral intention items, indicating that it is appropriate to keep all of the items as dependent measures. A summary of the results is shown in Table 6. TABLE 6 MANOVA Results for Model Significance for Basketball Behavioral Intention Items Source df F p Partial η Corrected Model Game attendance behavioral intention 7, 288 4.747 .000 .103 TV viewing behavioral intention 7, 288 5.354 .000 .115 Team clothing behavioral intention 7, 288 2.984 .005 .068 Basketball donor behavioral intention 7, 288 5.062 .000 2 .110 Discussion This study contributes to the crisis communication research using SCCT in a number of ways. First, it is part of an increasing number of studies in the public relations field that seek to experimentally test relevant factors in crisis communication. Second, it adds to the distinctions that are being made between related and combined crisis communication strategies, in this case by comparing an apology plus corrective action condition to a corrective action only condition. Third, by manipulating crisis severity, it helps increase the understanding of an important component of SCCT. Fourth, it confirms the importance of considering additional audience variables (e.g., identification) when managing crisis responses. Finally, it applied SCCT to a crisis involving a university sport program and helped to extend the potential for practical applications of the theory’s predictions. Evaluation of the first research question produced two different results based on the data analysis approach. The initial MANCOVA showed there was no significant difference between an apology plus corrective action and a corrective action only condition. This finding was 42 consistent with other research that has found apologies to not always be necessary (e.g., Coombs & Holladay, 2008), even under the circumstances when SCCT would predict an apology to be the best strategy (e.g., in response to a preventable crisis similar to the scenario used for this experiment). This result is practically useful for public relations practitioners helping to determine organization responses to crises. Apologies can make individuals or organizations legally responsible and susceptible to high financial risk. If similar strategies can successfully address the impact of a crisis, the knowledge is important to both the theory and the discipline. However, that non-significant finding was likely influenced by the decision to use a median split with the team identification independent variable. When the split was removed, a post hoc regression analysis showed that the apology manipulation was nearly significant (p = .05) with team supportive behavioral intentions as the dependent variable. The potential to impact this dependent variable is important. Coombs (2007) wrote about the need for SCCT to connect the effects of a crisis to behavioral intentions, stating that “if crises altered reputations and create affect but did not impact behavioral intentions, there would be no reason to worry about the effects of crises” (p. 169). This indicates that the positive impact of a carefully developed apology still has value, consistent with the original predictions of SCCT. The manipulation of crisis severity partially confirmed an SCCT prediction that crisis severity would produce a greater reputational threat. Surprisingly though, crisis severity impacted behavioral intentions (e.g., less likely to attend games, watch games on TV) but did not threaten the reputation of the basketball program. Typically, attitude change is more likely than behavioral change and in this instance the reverse was true. This finding can be understood by considering the nature of a crisis and the challenge of manipulating crisis severity in an experimental setting. It is important to develop high and low crisis severity manipulations that 43 are believable, but this also served to produce a reputational threat that was moderately strong, between four and five on a 7-point scale, for both crisis severity conditions. It is also possible that the lack of reputational threat could be a consequence of the student population. Students who are interacting primarily with other students may have less awareness of a reputational threat; conversely, older alumni who interact on a more frequent basis with graduates and fans of other universities could perceive a greater threat. A subsequent study should replicate the findings with an alumni or season ticket holder population to explore possible differences. The inclusion of audience identification in a study evaluating the effectiveness of SCCT in a university sport setting was important. Significant differences were found when evaluating both the reputation of the basketball program and the behavioral intentions of high and low identification students. This indicates that including the variable will improve crisis managers’ ability to anticipate audience responses. This finding confirms the value of using audience identification in SCCT research. It helps to establish that identification with a university basketball program is a worthwhile way to understand differential audience responses when evaluating the impact of crisis response strategies. The argument for the inclusion of this type of involvement variable that can influence SCCT was raised by Choi and Lin (2008). In addition, McDonald et al. (2010) confirmed the benefit of considering involvement as a way to explain audience reactions in crisis communication. In a recent study Coombs and Holladay (2011) discuss the importance of proper anticipation of people’s reactions to a crisis and the selection of effective crisis response strategies. The results of this study contribute to this growing area of study while emphasizing the type of variable inclusion that can improve anticipation of audience reactions. 44 Analysis conducted to answer the research question about the impact of the crisis on university donor intentions showed that this student audience separates the behavior of members of the basketball program from the university. Even though research has shown successful athletic programs can increase alumni contributions (Toma & Cross, 1998), a single crisis event does not appear to threaten university donor intentions. This result should be interpreted cautiously, however. Students were not asked if they intend to donate to the university or not in the future. The item should be added to future research to allow for better interpretation of the results. It is also possible that an older target audience that is currently donating to the university, or has donated in the past, may react differently than students on campus. Another empirical question would be to explore the cumulative impact of multiple crises involving a university sport program. SCCT predicts that a negative crisis history, as opposed to a single crisis, would produce a greater reputational threat. In a scenario where repeated crises happen, corrective action would be perceived as less effective (i.e., if it was working the crises would not continue to take place) and the responsibility attributions could extend beyond the sport program to the overall university. The application of SCCT in a scenario that involves a university sport program helps to extend its ability to explain crisis communication across subject areas. It has not previously been applied to a university sport program in published public relations research. As Coombs (2004) states in a recent article, the possibility exists “that the exact configuration of the crisis situation model (SCCT) may vary slightly from crisis cluster to crisis cluster, or crisis type to crisis type” (p. 286). If research continues to show SCCT’s predictions vary and related crisis response strategies produce equal or improved results, the case will be strengthened for revising the continuum approach initially described by Coombs (1998). 45 Ample opportunities exist for continued crisis communication research involving university sport programs, and work in this area is particularly timely considering recent crises involving members of football programs at Penn State, Ohio State, and the University of Miami. The results can improve the development of SCCT and will have practical applications for SIDs working in the field. Limitations Although experimental research with student participants is often criticized (e.g., Coombs & Holladay, 2009), the university sport focus of this project makes the student sample in this study appropriate and worthwhile. Stoldt et al. (2001) identified the student audience as an important one for university athletic departments and athletic directors identified weak perceived relationships with students as one that could be improved. For research involving university sport programs, the student audience provides a starting point before expanding to other relevant target audiences (e.g., alumni, season ticket holders, local community members). It is possible that student perceptions of a sport program and university are blurred because of their own current involvement in the university community. Hence, the eventual expansion to other audiences is prudent. Aside from the inclusion of a student sample, however, a valid limitation for this study is that the students were not a representative sample of all students at the university. Although the demographic characteristics of participants were similar to those of the university population, they were not selected from the entire population. The research participants were not actual stakeholders in a real-life crisis. In an effort to address this issue, the crisis scenarios were developed using media reports of crises that have occurred involving university sport programs. In addition, the university sport-oriented topic is 46 one that has widespread appeal among many university students, a high percentage of whom have indicated having at least some interest in major sports at their university (Taylor Research, 1998). Among the participants, 72% (213) had attended one or more basketball games at their university and 85.8% (254) had been a part of one or more sports teams in high school. Another limitation is that the crisis severity manipulation could have been improved. Although the difference between low and high severity conditions was statistically significant, the practical difference was still relatively small (about 1 on a 7-point scale) and both the low and high severity conditions were past the midpoint of the scale. It is challenging to develop a low severity crisis scenario that qualifies as a “crisis” while remaining realistic and believable. Finally, the participants did not perceive the basketball program’s reputational threat as distinct and different from the university’s reputational threat. This was a first attempt at adapting organizational reputation items developed by Coombs and Holladay (1996) to measure both an organization’s reputational threat and a subset of the organization’s reputational threat. It is possible that measurement error resulted in the items loading on the same factor and future work should seek to improvement this type of measurement. Future research A nature expansion of this research is to include other relevant target audiences for a university athletic department. Alumni, season ticket holders, and local community members are all among the possibilities. Their reactions may differ from students who have strong ties to the university that may influence their responses. Indeed, it may be hard to expect students who are paying significant amounts of money to attend a university to be overly critical of a university sport program from the same university. 47 It is worth further exploring how identification can help explain differential audience reactions. In a sport environment, it would be interesting to know if non-student fans of a university sport program respond in a similar manner. Intuitively, it seems possible that their identification may be lower than students currently attending the university and, consequently, a crisis may have a stronger impact on their attitudes and behavior. An extension of the research would be to apply it to the fans of a professional sports team. This may alter some of the high identification that exists in a university setting where students are an active part of the shared university environment and may be part of extremely active student fan sections that contribute to their overall social experience at the university. Continued research that compares related crisis response strategies is necessary to better understand the SCCT’s predictions. Instead of focusing on an instance where the university sport program is responsible, the opposite crisis type can be used to evaluate related defensive strategies. Finally, a better understanding of how target audiences perceive an apology would be useful. That is, do they accept the apology and believable and genuine or are there questions about its authenticity? Understanding this will help strengthen the results before practical advice can be offered to public relations practitioners suggesting they avoid an apology in a crisis situation. 48 APPENDICES 49 APPENDIX A The complete text of the four different scenarios used in the experiment is included below. Scenario #1 High Crisis Severity / Apology and Corrective Action Crisis Responses: Basketball Players Suspended, Coach Apologizes After OnCampus Theft Coach Bill Smith apologized today for his players’ behavior after he announced the suspensions of four university basketball players from all team activities. The players had pled guilty to felony burglary charges for breaking and entering and the theft of electronic equipment valued at $15,000. The stolen items included laptop computers, TVs, iPods, and DVD players from dorm rooms in a university residence hall. “On behalf of our basketball program, I would like to personally apologize for the actions of some of our players,” said the coach. The suspensions were determined by the coach and basketball program a short time after the players appeared in front of the county district court. “We expect our student-athletes to uphold a high standard of conduct on and off the field as representatives of this university,” said Coach Smith. “This type of behavior is disappointing and unacceptable.” According to university police, the equipment was taken from three different dorm rooms in a residence hall during a holiday break. All of the rooms were on the first floor and entry was obtained through unsecured windows. Students reported the missing equipment after returning from the break. Officers identified the athletes using electronic tracking technology and campus surveillance video. The felony charges result from stolen property valued greater than $2000. The sentencing date has not yet been determined. The university’s athletic director confirmed his support for the coach’s actions. “This type of behavior will not be tolerated at our university,” he said. “Our coach’s response should prevent this from happening again. Players need to know that their behavior has consequences.” Two of the players, both juniors, were starters on the basketball team and had played in all of the team’s games to date. The third was a sophomore playing a reserve role and the fourth was a redshirt freshman. Scenario #2 High Crisis Severity / Corrective Action Crisis Response: Basketball Players Suspended After On-Campus Theft Coach Bill Smith announced today the suspensions of four university basketball players from all team activities. The players had pled guilty to felony burglary charges for breaking and entering and the theft of electronic equipment valued at $15,000. The stolen items included laptop computers, TVs, iPods, and DVD players from dorm rooms in a university residence hall. 50 The suspensions were determined by the coach and basketball program a short time after the players appeared in front of the county district court. “We expect our student-athletes to uphold a high standard of conduct on and off the field as representatives of this university,” said Coach Smith. “This type of behavior is disappointing and unacceptable.” According to university police, the equipment was taken from three different dorm rooms in a residence hall during a holiday break. All of the rooms were on the first floor and entry was obtained through unsecured windows. Students reported the missing equipment after returning from the break. Officers identified the athletes using electronic tracking technology and campus surveillance video. The felony charges result from stolen property valued greater than $2000. The sentencing date has not yet been determined. The university’s athletic director confirmed his support for the coach’s actions. “This type of behavior will not be tolerated at our university,” he said. “Our coach’s response should prevent this from happening again. Players need to know that their behavior has consequences.” Two of the players, both juniors, were starters on the basketball team and had played in all of the team’s games to date. The third was a sophomore playing a reserve role and the fourth was a redshirt freshman. Scenario #3 Low Crisis Severity / Apology and Corrective Action Crisis Responses: Basketball Players Suspended, Coach Apologizes After OnCampus Theft Coach Bill Smith apologized today for his players’ behavior after he announced the suspensions of four university basketball players from all team activities. The players had pled guilty to misdemeanor burglary charges in the theft of TVs and iPods from dorm rooms in a university residence hall. “On behalf of our basketball program, I would like to personally apologize for the actions of some of our players,” said the coach. The suspensions were determined by the coach and basketball program a short time after the players appeared in front of the county district court. “We expect our student-athletes to uphold a high standard of conduct on and off the field as representatives of this university,” said Coach Smith. “This type of behavior is disappointing and unacceptable.” According to university police, the equipment was taken from three different dorm rooms in a residence hall during a holiday break. All of the rooms had been left unlocked and unattended. Students reported the missing equipment after returning from the break. Officers identified the athletes using electronic tracking technology and campus surveillance video. The misdemeanor charges result from stolen property valued greater than $200, but less than $1,000. The sentencing date has not yet been determined. The university’s athletic director confirmed his support for the coach’s actions. “This type of behavior will not be tolerated at our university,” he said. “Our coach’s response should prevent this from happening again. Players need to know that their behavior has consequences.” 51 Two of the players, both juniors, were starters on the basketball team and had played in all of the team’s games to date. The third was a sophomore playing a reserve role and the fourth was a redshirt freshman. Scenario #4 Low Crisis Severity / Corrective Action Crisis Response: Basketball Players Suspended After On-Campus Theft Coach Bill Smith announced today the suspensions of four university basketball players from all team activities. The players had pled guilty to misdemeanor burglary charges in the theft of TVs and iPods from dorm rooms in a university residence hall. The suspensions were determined by the coach and basketball program a short time after the players appeared in front of the county district court. “We expect our student-athletes to uphold a high standard of conduct on and off the field as representatives of this university,” said Coach Smith. “This type of behavior is disappointing and unacceptable.” According to university police, the equipment was taken from three different dorm rooms in a residence hall during a holiday break. All of the rooms had been left unlocked and unattended. Students reported the missing equipment after returning from the break. Officers identified the athletes using electronic tracking technology and campus surveillance video. The misdemeanor charges result from stolen property valued greater than $200, but less than $1,000. The sentencing date has not yet been determined. The university’s athletic director confirmed his support for the coach’s actions. “This type of behavior will not be tolerated at our university,” he said. “Our coach’s response should prevent this from happening again. Players need to know that their behavior has consequences.” Two of the players, both juniors, were starters on the basketball team and had played in all of the team’s games to date. The third was a sophomore playing a reserve role and the fourth was a redshirt freshman. 52 APPENDIX B Questionnaire instructions and items The first three items are based on the scenario you just read. Please mark your responses on the 1 to 7 scale that ranges from strongly disagree to strongly agree. 1. After the incident described in the scenario, the university’s basketball coach took action intended to prevent future incidents from happening again. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 2. On behalf of the basketball program, the coach apologized for his players’ actions. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 3. The crime described in the scenario is a severe problem for the basketball program. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree The next five items deal with different types of outcomes related to a university basketball program. Please mark your responses on the scale from strongly disagree to strongly agree. 4. If I were a student at this university, this incident would decrease the likelihood that I would attend its basketball games. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 5. If I were a student at this university, this incident would decrease the likelihood that I would watch its basketball games on TV. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 6. If I were a student at this university, this incident would decrease the likelihood that I would buy team clothing during the next few months. 1 2 Strongly disagree 3 4 Not sure 53 5 6 7 Strongly agree 7. If I were already an alum of this university, this incident would decrease the likelihood that I would donate money to support the basketball team. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 8. If I were already an alum of this university, this incident would decrease the likelihood that I would donate money to support an academic program at the university. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree The next 6 items deal with the impact this crisis may have on the University Basketball Program. Please mark your responses on the provided scale from strongly disagree to strongly agree. 9. The basketball program represented in this scenario is taking responsibility for its actions. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 10. Students at the university represented in this scenario should be proud of the basketball program’s reaction to this crisis. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 6 7 Strongly agree 11. The problem in this scenario occurs in most college basketball programs. 1 2 Strongly disagree 3 4 Not sure 5 12. The basketball program’s reaction will be viewed positively by the general public. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 13. The incident that occurred will affect the university’s reputation among the general public. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 14. Graduates of this university will be satisfied with the way the basketball program handled this crisis. 1 2 Strongly disagree 3 4 Not sure 54 5 6 7 Strongly agree The next six items deal with the impact this crisis may have on the University overall. The University’s Public Relations Office typically works with the Athletic Department to determine how to respond. Please mark your responses on the provided scale from strongly disagree to strongly agree. 15. The University represented in this scenario is taking responsibility for its actions. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 16. Students at the university represented in this scenario should be proud of the University’s reaction to this crisis. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 5 6 7 Strongly agree 6 7 Strongly agree 17. The problem in this scenario occurs in most Universities. 1 2 Strongly disagree 3 4 Not sure 18. The University’s reaction will be viewed positively by the general public. 1 2 Strongly disagree 3 4 Not sure 5 19. The incident that occurred will affect the University’s reputation among the general public. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 20. Graduates of this university will be satisfied with the way the University handled this crisis. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree The following open-ended question can help future research about crises and university basketball programs. Please write your response in the space provided. 21. Can you think of any crisis issues or scenarios that would result in you decreasing your support of your university’s basketball program? ______________________________________________________________________________ ______________________________________________________________________________ 55 The next six items are related to your opinion toward Michigan State University’s basketball program. Circle the number that best describes your agreement or disagreement with each of the following statements: 22) It is important to me to maintain strong ties to MSU’s basketball team. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 5 6 7 Strongly agree 23) Supporting MSU’s basketball team is important to me. 1 2 Strongly disagree 3 4 Not sure 24) One of the things I would tell others about myself is that I am a fan of MSU’s basketball team. 1 2 3 4 5 6 7 Strongly disagree Not sure Strongly agree 25) Being a basketball fan at MSU is an important part of who I am. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 26) I wear t-shirts, sweatshirts or hoodies that show my support for the MSU basketball team. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 6 7 27) I almost think of myself as part of MSU’s basketball program. 1 2 3 Strongly disagree 4 5 Not sure Strongly agree The next six items are related to your opinion toward MSU. Circle the number that best describes your agreement or disagreement with each of the following statements: 28) It is important to me to maintain strong ties to MSU. 1 2 Strongly disagree 3 4 Not sure 56 5 6 7 Strongly agree 29) Supporting MSU is important to me. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 30) One of the things I would tell others about myself is that I am a student at MSU. 1 2 3 4 5 6 7 Strongly disagree Not sure Strongly agree 31) Being an MSU student here is an important part of who I am. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 32) I wear t-shirts, sweatshirts or hoodies that show my support for MSU. 1 2 Strongly disagree 3 4 Not sure 5 6 7 Strongly agree 4 5 6 7 33) I almost think of myself as part of MSU. 1 2 3 Strongly disagree Not sure Strongly agree Please complete the following items about your background. 1. My gender is: (1) Female (2) Male 2. My ethnicity is: (1) White/Caucasian (2) Black/African American (3) Hispanic/Latino(a) (4) Asian/Pacific Islander (5) Other: _______________________ 3. My age is: ___________ 4. My class standing is: (1) Freshman (2) Sophomore (4) Senior (5) Graduate student (3) Junior 5. My major is: ___________________________________________________________ 57 6. Have you ever attended any of MSU’s basketball games? (1) No (2) Yes 6a. IF YES: On average, how many games do you go to during a season? ____________ 7. Are you currently affiliated with MSU’s basketball student section? (1) No (2) Yes 8. Were you ever affiliated with MSU’s basketball student section? (1) No (2) Yes 9. Were you a member of your high school’s basketball team? (1) No (2) Yes 10. Were you a member of any other sports team in high school? (1) No (2) Yes This concludes the survey. Thank you for your participation! 58 REFERENCES 59 REFERENCES Ashforth, B. E. & Mael, F. (1989). Social identity theory and the organization. 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