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Can service quality predict spectators’ behavioral


Managing Leisure 13, 162 –178 (July-October 2008)

Can service quality predict spectators’ behavioral intentions in professional soccer?
Nicholas D. Theodorakis and Kostantinos Alexandris
Department of Physical Education and Sport Science, Aristotle University of Thessaloniki, Serres, Greece
This study aims to examine if service quality dimensions can predict spectators’ behavioural intentions in the context of professional soccer in Greece. Data collected from two hundred and forty two (N 5 242) spectators, who were fans of a speci?c professional team. The SPORTSERV scale was used to assess service quality. Behavioural intentions were measured using the two subsets (repurchase intentions and word of mouth). The results of the con?rmatory factor analysis and the alpha scores provided evidence for the validity and reliability of the scale used. The personnel and reliability dimensions of service quality weakly but signi?cantly predicted repurchase intentions, while the tangibles, responsiveness and reliability dimensions predicted a signi?cant and moderate amount of variance in word-of-mouth communications. The practical and theoretical implications of these results are discussed.

INTRODUCTION Quality has been suggested as a key issue for the success of service organisations, since it is related to increased consumer loyalty and higher pro?ts for organisations (Backman and Veldkamp, 1995; Baker and Crompton, 2000; Dagger and Sweeney, 2006; Mittal and Kamakura, 2001; Rust et al., 2000; Verhoef, 2003; Zeithaml and Bitner, 2003). A customer with positive service quality perceptions is likely to report high levels of satisfaction and subsequently develop attitudinal and behavioural loyalty with the organisation and its services (Burton et al., 2003; Dagger et al., 2007; Keillor et al., 2007; Lee et al., 2007; Olorunniwo et al., 2006; Spreng and Chiou, 2002). While the link between service quality and consumer loyalty is well documented in the services marketing literature, it is not yet established in the sport spectators industry. This is due to differences between the purchase decision making of a general consumer

and a sport fan consumer; these differences relate to the important role of variables, such as team identi?cation (Robinson et al., 2005; Trail et al., 2003), fan motivation (Mahony et al., 2002; Robinson et al., 2004), involvement (Funk et al., 2002; Funk et al., 2004), and brand associations (Boyle and Magnusson, 2007; Ross, 2007) on spectators’ purchase decision-making process. While the above-mentioned variables have been shown to signi?cantly in?uence the development of fan loyalty, the role of service quality is still questionable. There have been some attempts to measure service quality in spectators’ sports (Dale et al., 2005; Kelley and Turley, 2001; McDonald et al., 1995; Theodorakis et al., 2001) and to examine the role of different service aspects on the development of positive spectators’ behavioural intentions (Brady et al., 2006; Hightower et al., 2002; Hill and Green, 2000; Wake?eld and Blodgett, 1994, 1996, 1999). The studies published so far did not provide a clear

Managing Leisure ISSN 1360-6719 print/ISSN 1466-450X online # 2008 Taylor & Francis http://www.tandf.co.uk/journals DOI: 10.1080/13606710802200852

Service Quality and Behavioral Intentions conclusion about whether service quality plays a role in the development of spectators’ loyalty. The purpose of the present study was to test the degree to which service quality dimensions predict spectators’ behavioral intentions, expressed by repurchase intentions and word-of-mouth communications. MEASURING SERVICE QUALITY Zeithaml and Bitner (2003) de?ned perceived service quality as a global judgment or attitude relating to the superiority of a service. It is widely accepted today that the measurement of service quality requires the application of multi-dimensional models. However, it has been also proposed that the nature and the number of the speci?c dimensions included in any model are contextually depending on the speci?c industry (Babakus and Boller, 1992; Teas and DeCarlo, 2004). In the leisure industry, studies could be categorized into those conducted in the contexts of (a) participatory sports and active recreation and (b) spectator sports. SERVICE QUALITY MODELS IN PARTICIPATORY SPORTS AND RECREATION A variety of models have been developed for the measurement of service quality in the context of participatory sports and active recreation. A detailed review of the sport and leisure literature indicates that there are seven service quality models that have been published so far. Almost all of these models have used the original SERVQUAL model (Parasuraman et al., 1988) as a base for development. Although some of these studies ended to similar factor structures, it can be argued that the lack of a widely accepted, valid, and reliable leisure service quality model is a major limitation of the leisure quality literature so far. Furthermore, since studies have been conducted in

163 different countries and continents (e.g., North America, England, Europe, and Australia), it would be expected that cultural aspects of consumer behaviour should have been controlled and considered. This, however, has not been done so far. A brief presentation of these service quality models will follow. The REQUAL model (Crompton et al., 1991; MacKay and Crompton, 1990) was one of the ?rst published and was developed for public recreation services in the USA. This model was also adjusted and further developed by Wright et al. (1992) and later by Backman and Veldkamp (1995). The REQUAL scale proposed a four-factor structure (assurance, reliability, responsiveness, and tangibles), which was similar to the SERVQUAL model (Parasuraman et al., 1988). This model was shown to be applicable in the context of public recreation services in the USA, but seemed not to be easily adjustable to sport services in other countries and sectors (private). The second model named QUESC (Quality Excellence of Sport Centers) was developed by Kim and Kim (1995) in the context of sport centres in Korea. This model consists of 12 context-speci?c service quality dimensions: ambience, employee attitude, employee reliability, social opportunity, information available, programmes offered, personal considerations, price, privilege, ease of mind, stimulation, and convenience. QUESC was a promising model in terms of being detailed and including a wide range of service quality dimensions. However, the authors did not present evidence regarding the construct validity of the scale. This was re?ected on the study of Papadimitriou and Karteroliotis (2000), who used QUESC to examine service quality in private ?tness centres in Greece. The results from an exploratory factor analysis suggested a different factor structure that includes four dimensions: instructor quality, facility attraction and operation, programme availability, and delivery of other services.

164 Based also on SERVQUAL model and its discon?rmation of expectations paradigm, Howat et al. (1999) developed the CERMCSQ (Center for Environmental and Recreation Management – Customer Service Quality). This model proposed three dimensions of service quality: core services, personnel, and peripheral services. Howat and Murray (2002) and Murray and Howat (2002) also used CERM-CSQ in the context of public recreation centres in Australia and New Zealand. The size of the scale, which is short, is one of the strong points of this model, which was also shown to have good predictive validity. CERM-CSQ has been popular among researchers in the context of public recreation centres in Australia and New Zealand. Taking into consideration the criticisms over SERVQUAL’s inadequacy to measure technical service quality (Brady and Cronin, 2001), Alexandris et al. (2004a, b) added the outcome dimension in the measurement of service quality. In this line, they suggested a ?ve-dimensional model (perceived outcome, responsiveness, tangibles, reliability, and personnel) for measuring service quality in the context of private ?tness centres in Greece. The outcome quality was shown by the authors to be an important dimension in predicting consumer behavioural intentions. In the same context (?tness), Chang and Chelladurai (2003) used a different conceptual approach in order to develop SQFS (Scale of Quality in Fitness Services). They proposed nine dimensions of service quality, which were judged by customers in the input, throughout, and output stages of ?tness service production process: service climate, management commitment, programmes, interpersonal interactions, task interactions, physical environments, other clients, service failure and recovery, and perceived service quality. This approach and the model developed did not attract the interest of others researchers so far. In the same context (?tness), Lam et al. (2005) proposed the

Theodorakis and Alexandris Service Quality Assessment Scale (SQAS). The SQAS model, in which the factorial validity was established with the use of Structural Equation Modelling (SEM), includes six dimensions of service quality: staff, programme, locker room, physical facility, workout facility, and childcare. A different methodology was applied by Ko and Pastore (2005), who developed a detailed measurement, called the Scale of Service Quality for Recreation Sport (SSQRS), with the aim of measuring the ?rst- and secondorder service quality dimension, based on previous work by Brady and Cronin (2001) and Dabholkar et al. (1996). This scale consists of 49 items, measuring 11 ?rst order dimensions of service quality: range of programmes, operating time, information, client–employee interaction, inter-client interaction, valence, sociability, physical change, ambiance, design, and equipment. According to the authors, these 11 dimensions correspond to four second order dimensions, namely programme quality, interaction quality, outcome quality, and physical environment quality. Recently, Ko and Pastore (2007) used SSQRS in the context of campus recreation sports. By reviewing the above-mentioned studies, it becomes clear that researchers in this area should build a dialogue and develop communication in order to agree to the adoption of one of the above models. The ?nal selected model should be crossvalidated in various participatory leisuresports contexts, and should be validated against behavioural and attitudinal aspects of participation. In addition, consumer culture should be among the variables considered for international communication and cross-cultural research. SERVICE QUALITY MODELS IN THE SPORT SPECTATORS CONTEXT Studies aiming to measure service quality in the sport spectator context are still limited. It should be noted that the contexts of

Service Quality and Behavioral Intentions participatory and spectatorship sports are different, due to the nature of consumer participation (active vs. passive) in the two contexts. Three models have been proposed so far, developed by McDonald et al. (1995), Kelley and Turley (2001), and Theodorakis et al. (2001). McDonald et al. (1995) presented TEAMQUAL in the context of professional basketball in the USA. They developed 39 contextspeci?c items, based on the ?ve original SERVQUAL dimensions (Tangibles, Reliability, Responsiveness, Assurance, and Empathy). TEAMQUAL used the expectancy discon?rmation approach, that is measuring simultaneously both expectations and perceptions of service, with one administration of the instrument. In addition, the scale included importance-weighted evaluations for each one of the ?ve service quality dimensions. The authors did not provide any additional information regarding TEAMQUAL’s psychometric properties. Kelley and Turley (2001) proposed a ninefactor service quality model that emerged from an exploratory factor analysis of 35 service attributes. This study was conducted in the context of collegiate basketball in the USA. The nine dimensions were: employees, price, facility access, concessions, fan comfort, game experience, show time, convenience, and smoking. The authors did not provide any information regarding the internal consistency reliabilities of the nine service quality dimensions. Finally, the third study was conducted by Theodorakis et al. (2001) in the context of professional basketball in Greece. They used SPORTSERV, which is a 22-item scale, consisting of ?ve dimensions, namely Tangibles, Responsiveness, Access, Security, and Reliability. This scale was originally developed in the doctoral dissertation of one of the authors (Theodorakis, 2000). The validity (factorial, predictive, and discriminant) and reliability of this scale were established with the use of appropriate statistical techniques.

165 In conclusion, it is clear that more research is required in order to establish a valid and reliable service quality model in spectator sports. It is an industry with tremendous social and economic impact internationally, especially in Europe (Andreff and Staudohar, 2000). Professional soccer is a sport with high popularity among Europeans, with enormous economic growth in the last 20 years (Andreff, 2007; Ascari and Gagnepain, 2006; Baroncelli and Lago, 2006; Frick and Prinz, 2006). It is, therefore, expected that more emphasis should be given in the future on the development of a uni?ed and valid service quality model. A comprehensive list of all service quality models discussed above is presented in Table 1. SERVICE QUALITY AND BEHAVIOURAL INTENTIONS Starting from the de?nition of ‘consumer behavioural intentions,’ we should refer to the work by Zeithaml et al. (1996), in which a multi-dimensional model of behavioural intentions was proposed. It was suggested that favourable behavioural intentions include elements such as saying positive things and recommending the service to others, paying a price premium to the company, and expressing cognitive loyalty to the organization. In the present study, we have used purchase intentions (intention to watch football games of the speci?c team in the future) and word-of-mouth communications (intention to say positive things about the team and its services), as the two dimensions of spectators’ behavioural intentions. Establishing a link between service quality and consumer behavioural intentions is an important task for researchers and practitioners, since it is evidence for the value of service quality research. This link has been well established in the participatory sports and leisure literature, but it is not

166
Table 1 Service quality models in sport and leisure settings Authors MacKay and Crompton (1990) Model REQUAL Number of dimensions 4

Theodorakis and Alexandris

Name of dimensions Assurance, reliability, responsiveness, tangibles

Context Participatory sports and active recreation

Kim and Kim (1995)

QUESC

12

Howat et al. (1999) Alexandris et al. (2004a) Chang and Chelladurai (2003)

CERM-CSQ —

3 5

SQFS

9

Lam et al. (2005)

SQAS

6

Ko and Pastore (2005)

SSQRS

4

McDonald et al. (1995) Kelley and Turley (2001)

TEAMQUAL

5



9

Theodorakis et al. (2001)

SPORTSERV

5

Ambience, employee attitude, employee reliability, social opportunity, information available, programs offered, personal considerations, price, privilege, ease of mind, stimulation, convenience. Core services, personnel, peripheral services Perceived outcome, responsiveness, tangibles, reliability, personnel Service climate, management commitment, programs, interpersonal interactions, task interactions, physical environments, other clients, service failure, recovery. Staff, program, locker room, physical facility, workout facility, childcare Program quality, interaction quality, outcome quality, physical environment quality Tangibles, responsiveness, reliability, assurance, empathy Employees, price, facility access, concessions, fan comfort, game experience, showtime, convenience, smoking. Tangibles, responsiveness, access, security, reliability

Spectator sports

yet clear in the sport spectators’ context (Cronin et al., 2000; Hightower et al., 2002). Furthermore, the relationships between speci?c service quality dimensions and

behavioural intentions are not yet clear, due to the different service quality models used and the different contexts of the published studies. As a general conclusion, it

Service Quality and Behavioral Intentions could be argued that these relationships are contextual, depending on the speci?c characteristics of each industry. This was made clear in the study of Bloemer et al. (1999). They reported that in the entertainment industry, word of mouth was positively affected by responsiveness and tangibles, whereas in the food service industry, it was positively affected by assurance and empathy. Furthermore, behavioural intentions were determined by reliability in the entertainment industry and by assurance and empathy in the food industry. Wake?eld and Blodgett (1999), who used multi-dimensional models of both quality and behavioural intentions, carried out a study in three different leisure settings (professional hockey games, a recreation centre, and movie theatres). They reported that service quality had a positive effect on customers’ repatronage intentions and their willingness to recommend the leisure organization to others. These researchers also noted that intangible service factors (reliability, responsiveness, empathy, and assurance) were better predictors of customers’ behavioural intention than the tangible factors of service (facility design, ambience, and equipment). Similar results were presented by Alexandris et al. (2001), who conducted a study in the context of ?tness in Greece, and by Baker and Crompton (2000), who conducted a study in the tourism sector. Alexandris et al. (2001) reported that service quality dimensions signi?cantly predicted favourable behavioural intentions (repurchase intentions and word-of-mouth communications). However, in their study, the dimensions of service quality failed to predict complaining behaviour and price sensitivity. Baker and Crompton (2000), using structural modelling design, provided evidence that service quality dimensions (adjusted to the context of tourism events) were directly and positively related with purchase intentions, customer loyalty, and willingness to pay more money. Finally, Murray and Howat (2002) conducted a study

167 in the context of public leisure centres, in an attempt to investigate the relationships between quality, satisfaction, perceived value, and behavioural intentions. Results provided evidence for the indirect link between service quality and behavioural intentions. Two studies have examined so far the in?uence of service quality on behavioural intentions in spectator sports. Cronin et al. (2000) used structural equation modelling to investigate the effects of service quality, customer satisfaction, and value on spectators’ behavioural intentions. They found that quality, satisfaction, and value had both direct and indirect effects on spectators’ behavioural intentions. Hightower et al. (2002), on the other hand, using similar statistical techniques, found that service quality had an indirect effect on behavioral intentions through perceived value. In addition, there have been some other studies (Hill and Green, 2000; Wake?eld and Blodgett, 1994; 1996) which focused on the physical aspect of service quality (servicescape) and examined its relationship with spectators’ behavioural intentions. They all provided evidence for the link between the physical environment quality (i.e., servicescape) and consumer behavioral intentions. It should be emphasized here that the vast majority of the above studies were conducted in the context of North American spectator sports, with only one study conducted in Australia (Hill and Green, 2000). The transfer of the above results to Europe is questionable, due to the cultural differences of the fans and the different characteristics of sport leagues among continents. OBJECTIVES OF THE STUDY This study aimed to test (a) the validity and reliability of SPORTSERV, in the context of professional soccer in Greece and (b) the degree to which service quality dimensions can predict spectators’ repurchase intentions and word-of-mouth communications.

168 Methodology Professional soccer in Greece According to the Greek State Law, three sports (football, basketball, and volleyball) have professional status in Greece. Soccer is by far the most popular sport in Greece. Greek professional soccer is organized into three national divisions and holds a 2% share of the European League football market, with an estimated total value of 10 billion euros (Deloitte and Touche, 2002). Two leagues represent all the professional Greek football teams. The Union of the Professional Teams represents 54 teams from the second and third divisions, and the Super League represents the top 16 teams from the ?rst division. These top 16 football teams come currently from nine Greek cities. The Super League was established in August 2006, in order to provide the highest standards for the organization of the ‘Super League Championship’, to promote football and its image in Greece, to increase involvement with the sport, to increase attendance, and to maximize pro?ts for its stakeholders, which are the 16 professional teams. During the 2005 – 2006 football season, the average attendance for each game was 5643 spectators, while in the 2006 –2007 football season, the average attendance was 6186 spectators, representing an increase of 9.63%. During the 2006 – 2007 football season, the ?rst team in ticket sales had an average attendance of 22,853 spectators per game. Overall, during the 2006 –2007 football season, a total number of 1,484,719 spectators attended games of the Super League Championship, covering 27.3% of the stadiums’ capacities. Sample and data collection 242 (N ? 242) spectators, who attended a football game of the Super League in Greece, participated in the study. 320 questionnaires were distributed in total in the stadium, and 242 were collected back,

Theodorakis and Alexandris achieving a response rate of 75.6%. In order to ensure representation of all fans in the stadium (Robinson et al., 2005), eighty questionnaires in each of the four major parts of the stadium were distributed. All questionnaires were collected prior to the beginning of the football game, at the time fans were taking their seats in the stadium, by a team of six experienced interviewers and one supervisor. In terms of the gender of the sample, 204 (84.3%) were males and 36 (14.9%) were females, while two spectators did not report their gender. Their mean age ranged from 18 to 64 years, with a mean age of 33.67 years (SD ? 9.46). Measures Service quality To assess spectators’ perceptions of service quality, the SPORTSERV was used (Theodorakis, 2000; Theodorakis et al., 2001). SPORTSERV includes 22 items. Two items (quality of air in the stadium and undistracted view from the seat) were deleted because they faced content validity problems with the particular context of the study (open stadium instead of indoor facility). The 20 remaining items measured ?ve dimensions: Tangibles (four items, e.g., the stadium is visually appealing, cleanliness of the facility), personnel (four items, e.g., personnel providing prompt service, personnel willingness to help), security (four items, e.g., feeling safe inside the stadium, team provides high standards of security during games), access (four items, e.g., accessibility of/to the stadium, parking availability), and reliability (four items, e.g., team delivers its services as promised, team provides its services right the ?rst time). The scale includes only perceptions-performance statements, measuring service quality at the macro level. Previous studies (Cronin and Taylor, 1992; Dabholkar et al., 2000; Parasuraman et al., 1994) have supported the predictive value

Service Quality and Behavioral Intentions of using perception items, as opposed to using expectation statements (i.e., computed discon?rmation, measured discon?rmation). Earlier research ?ndings also indicated that the expectation-discon?rmation frameworks faced several theoretical and empirical shortcomings (Babakus and Boller, 1992; Brown et al., 1993; Iacobucci et al., 1994; McDougall and Levesque, 1994; Teas, 1993). A seven-point Likert type scale was used (1 strongly agree to 7 strongly disagree). Behavioral intentions To determine spectators’ behavioral intentions, two subscales proposed by Zeithaml et al. (1996) were used: word-of-mouth communications (three items, e.g., saying positive things about the team to others) and repurchase intentions (three items, e.g., attending more games in the near future). For both scales, responses were given on a seven-point Likert type scale ranging from 1 (very unlikely) to 7 (very likely). Evidence regarding these subscales’ validity and reliability has been provided in previous published studies (Alexandris et al., 2001; Bloemer et al., 1999; de Ruyter et al., 1998). Data analysis To examine the factorial validity of SPORTSERV, a con?rmatory factor analysis (CFA) (Ullman, 1996) was performed, using the EQS (Bentler, 1995). To test, if all variables were normally distributed, an exploratory data analysis based on the inspection of skewness values, kurtosis values, and the Kolmogorov-Smirnov test of normality was conducted. To assess the ?t of CFA models, researchers have developed and presented a great number of ?t indices (Stevens, 2002). In this study, the ?t indices used for model evaluation were the Sattora-Bentler scaled x 2 statistic (x 2), the Non-Normed Fit Index (NNFI), the robust Comparative Fit Index (CFI), and the Root Mean Square Error of Approxiamation (RMSEA).

169 Generally, for NNFI and CFI, values greater than 0.90 indicate an acceptable ?t between the observed data and the hypothesized model (Hu and Bentler, 1995), while values greater than 0.95 indicate an excellent ?t (Hu and Bentler, 1999). RMSEA values ranging from 0.06 to 0.08 declare an adequate ?t with 0.10 to be considered as the upper limit (Byrne, 2000). To examine the relationship between perceived service quality and behavioural intentions, two multiple regression analyses were performed. The ?ve service quality dimensions were set as the independent variables in both of them, and behavioural intentions (word of mouth and repurchase intentions) were used as the dependent variable separately. Results Descriptive statistics and reliability Descriptive statistics for all variables are presented in Table 2. As shown, the responsiveness (M ? 4.3), access (M ? 4.3), Security (M ? 4.4), and reliability (M ? 4.7) dimensions achieved moderate mean scores. Spectators’ perceptions about the tangible (M ? 3.3) aspect of service quality were not positive. Spectators’ willingness to attend team’s games in the future had a somewhat high mean score (5.4), while their willingness to say positive things about the team and its services to others had a moderate mean score (4.8). The Cronbach’s alpha values for all service quality and the two behavioural intentions dimensions were satisfactory (.0.73). Composite reliabilities were computed for the ?ve service quality dimensions. All values indicated good levels of reliability exceeding the 0.60 threshold suggested by Bagozzi and Yi (1988). CFA The univariate skewness values of the scale ranged from 20.71 to 0.45. The

170

Theodorakis and Alexandris

Table 2 Means, standard deviations, alpha values, and correlations for repurcase intentions, W.O.M., and service quality dimensions Variables Repurchase Intentions W.O.M. Tangibles Responsiveness Access Security Reliability
?

M 5.43 4.81 3.32 4.34 4.32 4.48 4.74

SD 1.42 1.56 1.70 1.75 1.74 1.72 1.48

A 0.72 0.82 0.86 0.93 0.93 0.90 0.91

Composite reliabilities

AVE

r

0.87 0.93 0.93 0.91 0.92

0.67 0.82 0.80 0.76 0.78

0.58? 0.03 0.21? 0.01 0.18? 0.23?

0.44? 0.39? 0.28? 0.41? 0.45?

0.50? 0.43? 0.49? 0.45?

0.22? 0.44? 0.48?

0.37? 0.34?

0.55?

0.01 level.

vuniariate values for kurtosis ranged from 21.26 to 20.27 (Table 3). An exploratory analysis of the above values along with the use of the Kolmogorov-Smirnov test of normality showed that all variables were not normally distributed. The Mardia’s coef?cient (Mardia, 1970) of multivariate kurtosis was 132.12, and the normalized estimate was 34.13. Byrne (2006) suggested that normalized estimate values greater than ?ve indicate departures from normality. Thus, it seemed that the assumption of multivariate normality was not tenable. Based on the above, it was decided to use the Sattora-Bentler scaled x2 statistic. Results indicated an acceptable ?t of the model to the data: S-B x2 ? 324.25, df ? 160, p , 0.001, S-B x2/df ? 2.02, NNFI ? 0.945, CFI ? 0.954, RMSEA ? 0.066, 90% RMSEA CI ? 0.063 2 0.077. The scale also demonstrated satisfactory convergent validity, since (a) all standardized factor loadings were above 0.707 (Fornell and Larcker, 1981), (b) items loadings had signi?cant t-values ranged from 12.44 to 19.66 (Anderson and Gerbing, 1988), and (c) average variance extracted (AVE) for all constructs exceeded the 0.50 cut off (Fornell and Larcker, 1981) (Table 2).

Predicting Word of Mouth The degree to which word of mouth can be predicted by the ?ve service quality dimensions was tested in the ?rst regression model (Table 4). The regression analysis produced a signi?cant effect (F ? 19.8, p , 0.001). The dimensions of Tangibles (Beta ? 0.19, t ? 2.60, p , 0.001), Responsiveness (Beta ? 0.13, t ? 1.94, p , 0.05), and Reliability (Beta ? 0.20, t ? 2.92, p , 0.01) had signi?cant contributions. The three dimensions together predicted 30% of the variance in word-of-mouth Communications. Predicting fans’ repurchase intentions The second regression analysis was conducted to examine the degree to which fans’ repurchase intentions can be predicted by the ?ve service quality dimensions. The regression analysis produced a signi?cant effect (F ? 4.40, p , 0.001). However, only the dimensions of Personnel (Beta ? 0.16, t ? 2.13. p , 0.05) and Reliability (Beta ? 0.16, t ? 2.06, p , 0.95) offered signi?cant contributions. The two dimensions together accounted for a 9% of the variance on Repurchase Intentions (Table 4).

Service Quality and Behavioral Intentions
Table 3 Descriptive statistics and CFA item statistics of SPORTSERV Variables Tangibles Item 1 Item 2 Item 3 Item 4 Responsiveness Item 5 Item 6 Item 7 Item 8 Access Item 9 Item 10 Item 11 Item 12 Security Item 13 Item 14 Item 15 Item 16 Reliability Item 17 Item 18 Item 19 Item 20
a

171

M 3.46 3.44 3.19 3.31 4.37 4.18 4.45 4.37 3.89 4.30 4.60 4.53 4.83 4.34 4.19 4.364 4.86 4.68 4.70 4.71

SD 2.08 2.04 1.97 1.97 1.19 1.89 1.92 1.94 1.91 1.91 1.85 1.88 1.87 1.95 1.94 1.90 1.59 1.67 1.69 1.67

t-values Skewness Kurtosis Factor loading Error term SMCsa 12.44 12.38 15.97 15.18 16.67 16.32 18.11 16.19 13.64 16.45 19.34 19.66 14.93 16.32 15.47 16.01 13.46 16.26 18.21 17.35 0.20 0.32 0.45 0.31 20.40 20.32 20.48 20.48 20.02 20.27 20.40 20.41 20.71 20.38 20.27 20.50 20.50 20.50 20.51 40 21.26 21.21 21.03 21.14 20.95 21.07 20.86 20.89 21.15 20.27 20.93 20.93 20.67 20.98 21.08 20.79 20.33 20.35 20.58 20.46 0.729 0.727 0.866 0.838 0.874 0.863 0.918 0.858 0.762 0.862 0.948 0.957 0.820 0.868 0.840 0.858 0.760 0.861 0.922 0.896 0.684 0.687 0.500 0.546 0.486 0.506 0.396 0.513 0.648 0.507 0.317 0.290 0.572 0.496 0.543 0.519 0.650 0.508 0.387 0.444 0.532 0.528 0.750 0.702 . 0.764 0.744 0.844 0.737 0.583 0.744 0.895 0.916 0.678 0.751 0.700 0.733 0.578 0.741 0.850 0.803

Squared multiple correlations.

DISCUSSION The leisure service quality academic literature has been growing in the last 10 years.

Theoretical models and frameworks, such as the SERVQUAL model, were adopted from the general marketing literature, were

Table 4 Regression analysis for repurchase intentions and word of mouth Repurchase intentions Beta Tangibles Responsiveness Access Security Reliability t p-value Beta Word of mouth t p-value

20.14 21.71 n.s 0.16 2.13 0.05 20.06 20.91 n.s 0.11 1.43 n.s 0.16 2.06 0.05 R 2 ? 0.09 F(5.228) ? 4.40 p , 0.001

0.19 2.68 0.05 0.13 1.99 0.05 0.05 0.79 n.s 0.12 1.72 n.s 0.20 2.92 0.05 R 2 ? 0.30 F(5.228) ? 19.820 p , 0.001

n.s., not signi?cant.

172 applied in the leisure context, and are further developed with the aim of capturing the speci?c characteristics of the leisure industry. Furthermore, critical reviews (Robinson, 2006) were published aiming to advance the theory and propose future directions for research. This increasing interest in service quality research is justi?ed by the practical value of ?ndings in this area. The changing nature of consumer needs and the increased competition make the investment on quality improvement more necessary today than ever. However, as O’ Neil et al. (2000, p. 137) pointed out, ‘a sustained and continuous quality improvement is not possible without some indication of quality performance’. Based on the above notion, this study aimed to establish a model for measuring service quality performance in the context of professional soccer and further examines whether service quality can predict spectators’ behavioural intentions. In terms of the ?rst objective, the results indicated that the adopted SPORTSERV scale, which was originally developed by Theodorakis et al. (2001), is a valid and reliable tool. The construct validity of the scale was supported by the con?rmatory factor analysis; furthermore, the alpha values indicated acceptable reliability levels. Subsequently, SPORTSERV is a useful tool that can be used by football club managers and marketers in their effort to measure the quality of their services. As previously noted, while the link between service quality and consumer behavioural intentions in the service marketing literature is well established (Athanassopoulos et al., 2001; Cronin et al., 2000; Dagger et al., 2007; Zeithaml et al., 1996), this relationship is not yet clear in the context of spectator sports. Only two studies so far, conducted in the USA (Cronin et al., 2000; Hightower et al., 2002), provided some evidence that service quality might have direct or indirect effects on spectators’ behavioral intentions. The results of the present

Theodorakis and Alexandris study provided limited support of the relationship between service quality and spectators’ repurchase intentions. The regression analysis indicated that service quality predicted only 9% of spectators’ repurchase intentions. Only two dimensions (personnel and reliability) offered signi?cant contributions to this prediction. This ?nding is in contrast with previous research, conducted in the general services marketing literature (Dagger et al., 2007; Keillor et al., 2007). It also points out the unique characteristics of the spectator, as a consumer, and the professional football, as a service context. There are more variables, such as fan identity, fan motivation, and brand associations (Funk et al., 2004; Mahony et al., 2002; Robinson et al., 2004) that in the case of the spectator consumer are likely more important factors for the prediction of spectators’ repurchase intentions than service quality. The weak relationship between service quality and repurchase intentions revealed in the present study also shows the dif?culties in managing and marketing sport clubs. Building on service quality is not enough to increase consumer/spectators’ retention levels. Service quality does not guarantee consumer/spectators’ loyalty. Future service quality research should incorporate variables, such as fan identity, brand associations, and fan satisfaction in an integrated model, in order to examine their interactions and in?uence on spectators’ repurchase intentions. Another possible explanation for the weak relationship between service quality and repurchase intentions might be related to the conceptualization of service quality. In this study, the ?ve service quality dimensions were all referred to the peripheral aspects of the sport product (i.e., prompt service, supportive services), and not to the core product (i.e., the game itself). It seems likely that aspects of the core product, such as a team’s performance or the outcome of the game, might have a

Service Quality and Behavioral Intentions strong effect on sport fans’ decisions to attend a game. To overcome this limitation, researchers should include an outcome dimension within the service quality models. In a recent study, Brady et al. (2006) found that valence (i.e., an assessment of the outcome) had a stronger effect on spectators’ satisfaction than functional and service environment quality. Commenting on the two individual service quality dimensions that offered some contribution to the prediction of repurchase intentions, it should be noted that they both refer directly (personnel) or indirectly (reliability) to the human element of the service organization. These results are in line with previous ?ndings of Wake?eld and Blodgett (1999), who also found that the human aspect of the service elements were the strongest predictors of customers’ intentions to repatronage the service in three different leisure settings. The personnel dimensions refer to the service provided by employees during the game day. This includes safety and security issues, instructions about spectators’ seating, and serving aspects in some special areas of the stadium, where members and season ticket holders are served. The personnel dimension is also evaluated against employees’ attitudes and behaviour on contact points and transactions related to buying tickets and giving face-to-face or over the phone information about the activities of the team. The building of this dimension is particularly applicable in Greece, where the majority of football clubs service employees are not well-trained in service skills. The second dimension that was shown to be related with repurchase intention (reliability) refers to the feelings of ‘fairness’ created to the fans by the credibility of the team administration and the employees. It is also built on the ability of the management of the club to keep its promises regarding the goals of the teams, the transfers of players, and the good coaching.

173 While the relationship between service quality and repurchase intentions was rather weak, the results showed that service quality dimensions predicted a signi?cant amount of variance (30%) of spectators’ willingness to recommend the team and its services to other people. This ?nding provides evidence for the value of service quality research in the context of professional football organizations. Word of mouth is one of the most important communication strategies for sport service organizations (Alexandris et al., 2001). A recent survey in Greece by the research company Nielsen revealed that almost 78% of Greeks considered word of mouth as the most credible source of any other form of marketing communications (Daily fax, 2007). In terms of the individual dimensions that contributed to the prediction of word of mouth, the results indicated that the tangible, reliability, and responsiveness made signi?cant contributions. These results are in line with previous studies conducted in leisure settings (Alexandris et al., 2001; Hightower et al., 2002; Cronin et al., 2000; Wake?eld and Blodgett, 1999). Regarding the role of the physical environment quality on spectators’ willingness to recommend the team and its services, it is to be noted that sport marketing writers have emphasized on the tangible aspect of the service, as one of the most important elements of the marketing mix (‘the place’ – the stadium) (Mullin et al., 2007). The stadium is the place where the sport product (i.e., the game) is produced and consumed simultaneously by the sport consumer. Since sport marketers lack control over the core sport product (outcome of the game), they should focus on peripheral aspects of the service, such as facility design and ambience conditions, cleaningless of the facility, personnel appearance and behaviour, and supportive services, such as restaurants and cafes. One of the unexpected ?ndings of the study was the non-relationships between

174 the access and security dimensions with any of the two dimensions of behavioural intentions. This is probably due to the sample of the study. The data were collected in a mid-sized city, in which spectators did not face major transportation problems. Furthermore, it seems that security might be a problem only in speci?c matches, where the outcome of the game is particularly important, and/or the fans of the opposite team are willing to follow their favourite team. In conclusion, the present study provided evidence that, in contrast to the general services marketing literature, the relationship between service quality and spectators’ repurchase intentions in the context of professional soccer is weak and limited to the dimensions of personnel and reliability only. However, service quality is an important predictor for the development of wordof-mouth communications, which is an important marketing strategy for all the service organizations. Limitations and Future Research The present study used data collected from a speci?c professional team in Greece. Results should be con?rmed with more data, collected from different teams in order to be generalized with more con?dence. Furthermore, as previously noted, the cultural aspects of the sport fans in different countries might in?uence the results and the conclusions of each study. This creates dif?culties in comparing research conducted in different countries. Cross-cultural research should be conducted in the future in order to control for cultural aspects of fans and help marketers and academics understand the similarities and differences in the decision-making process of fans internationally. A last issue that should be pointed out relates to the weak relationships between service quality and repurchase intentions revealed in the present study. Future research should incorporate within

Theodorakis and Alexandris service quality model factors that have been shown to signi?cantly predict spectators’ loyalty, such as fan identity, motivation, involvement, and brand associations.

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