Need for the Study

Considering its high global television ratings and broad international media coverage, the Formula One (F1) Grand Prix is one of the most influential sporting events in the world (Kim, Byon, Yu, Zhang, & Kim, 2013). Accordingly, the F1 Chinese Grand Prix, which launched in Shanghai in 2004, has become one of the main annual international sporting events in China, effectively increasing Shanghai’s reputation and attracting more global media attention. The high cost of hosting the F1 Grand Prix nevertheless creates a burden for host cities. According to the Formula Money Report (Formula Money Report, 2014), most cities hosting F-1 events have a difficult time earning a profit because the hosting fee alone is more than $568 million. Some host cities, such as Melbourne, have received substantial government funding to stage the F-1 Grand Prix, raising public questions about the value of hosting the event (Fairley, Tyler, Kellett, & D’Elia, 2011). As the only host city for F-1 events in China, Shanghai faces the same financial pressure caused by the high cost of the event, including the high hosting fees, high operation fees and high expenses of building the Shanghai International Circuit (Kim et al., 2013). Consequently, the Chinese Grand Prix has reported a nearly $30 million deficit every year (Xinhua, 2014).

According to the literature, while behavioral intention (e.g., Revisit intention) represents a willingness of performing a certain activity, word-of-mouth (WOM) is a expression of a communication regarding products, services, or brand from consumers (Grewal, Krishnan, Baker, & Robin, 1988; Kwon, Trail, & James, 2007). In addition, WOM plays a significant role in decision making process with the growth of Internet platforms such as social media (Lang, & Hyde, 2013; Mangold & Faulds, 2009). Thus, analyzing the factors that affect spectators’ behavioral intentions, such as revisit intention and WOM, will provide valuable data for marketers to establish practical marketing strategies that generate revenue. In addition, study of the F-1 Chinese Grand Prix will provide a better understanding of the Chinese sports market and spectators that possibly have unique characteristics with the Confucianism and Communism. Therefore, this study attempts to identify the effect of service quality on behavioral intentions in the context of the F-1 Chinese Grand Prix based on the previous studies indicating a positive relationship between service quality and behavioral intentions (Goldenberg, Libai, Moldovan, & Muller, 2007; Theodorakis & Alexandris, 2008).

Service Quality

One of the most important and widely studied factors in the marketing and service literature (Parasuraman, Zeithaml, & Malhotra, 2005), service quality is explained as the perceived level of excellence ascribed to a product or the degree to which actual service meets customer expectations (Parasuraman, Zeithaml, & Berry, 1988). In particular, researchers in sport management define service quality as interactions between consumers and organization and overall perceptions in the sporting circumstances such as seat available, layout, convenience, comfort, and information signs in a certain stadium (Brady & Cronin, 2001; Cronin & Taylor, 1992; Greenwell, Fink, & Pastore , 2002; Wakefield & Blodgett, 1996). Based upon the definitions, service quality comprises two significant dimensions including service that customers actually receive, such as the game result or athlete performance in a sports context (e.g., technical quality), and manner in which the service is delivered (functional quality) (Grönroos, 1984). For example, consumer’s perceived services from personnel in a certain sport stadium could significantly influence their responses such as the development of positive emotions about the team as well as intention to purchase tickets for future decisions (Brady & Cronin, 2001; Cronin & Taylor, 1992; Wakefield & Blodgett, 1996). In addition, particular environment around seating space, functions, and technologies positively contributes consumers’ evaluation, which directly influence overall perception as well as team involvement (Brady & Cronin, 2001; Kahle, Aiken, Dalakas, & Duncan, 2003). According to a research by Hill and Green (2000), they examined the relationships between consumers’ perception of service quality and intention for future decisions to participate the game in future in rugby league stadiums. Finally, they indicated that consumers who received positive services through employees and product usages in the stadium circumstances positively drive consumers’ emotions and a willingness of future behaviors (Hill & Green, 2000).

Service Quality and Behavioral Intentions

According to Ajzen (1991), “intentions are assumed to capture the motivational factors that influence a behavior” (p. 182), and behavioral intentions are thus regarded as a reliable predictor of actual behavior (Ajzen, 1991). Prior research has identified a positive relationship between service quality and behavioral intentions (Crompton, MacKay, & Fesenmaier, 1991; Goldenberg et al., 2007; Kuo, Wu, Deng, 2009; Theodorakis & Alexandris, 2008; Wakefield & Blodgett, 1996; Woodside, Frey, Daly, 1989). For instance, Kuo et al. (2009) found that customer satisfaction mediates the effect of service quality on repurchase intention. Analyzing consumers from two minor league baseball games and five major college football games, Wakefield and Blodgett (Wakefield & Blodgett, 1996) found that service quality has an indirect effect on behavioral intentions, as mediated by satisfaction. Among behavioral intentions, revisit intention in particular is considered an important factor associated with profit in various markets (Saha, 2009). Regarding the effect of service quality on revisit intention, Theodorakis and Alexandris (2008) found a direct effect of service quality on revisit intention by analyzing 242 spectators of football games in Super League Greece.

Service Quality and Word-of-Mouth

In addition to revisit intention, WOM is also considered an important factor associated with profit in various markets (Saha, 2009). Interpreted as the diffusion of information about products or services through customers (Saha, 2009), WOM is regarded as a reliable external source of information for customers (Saha, 2009). Previous studies have found a positive relationship between service quality and WOM. For example, in their study of Super League Greece spectators, Theodorakis and Alexandris (2008) also found that service quality has a direct effect on WOM. In addition, Kwon et al. (2013) found that service quality has a positive effect on WOM that is mediated by satisfaction in their study on the 2011 IAAF World Championship.

Participants

A total of 800 spectators from the F1 Chinese Grand Prix venue were invited to participate in a survey by using the convenience sampling method between April 15 and 17, 2010, in Shanghai. A total of 552 surveys were returned, a response rate of 69%. One survey was discarded owing to excessive missing values. Therefore, a total of 551 surveys were analyzed for this study. Of the research participants, men accounted for 57.0% (n = 314), and women accounted for 43.0% (n = 237). Most of the participants ranged in age from 21 to 30 years (58.6%; n = 323).

Instrument

Items measuring service quality were adopted and developed from Kwon, Kim, and Park (2013). Kwon et al. (2013) proposed six dimensions of service quality for an international sporting event based on prior studies (Lee, 2009; Ormiston et al., 1998; Parasuraman et al., 1988). Kwon et al.’s study (2013) indicated that the items measuring these dimensions have acceptable reliability according to Schuessler (1971), with Cronbach's alpha values greater than .60. Thus, following Kwon et al. (2013), this study measured service quality based on six dimensions: convenience, facilities, price, game experience, promotion, and staff. Six items measuring revisit intention and WOM were adopted from Choi, Kim, and Kwon (2011). Previous studies (Choi et al., 2011) have shown that these items have acceptable reliability, with Cronbach’s alpha values ranging from .77 to .92. All the items in the survey were measured on 5-point Likert scales ranging from 1 (strongly disagree) to 5 (strongly agree). These items were reviewed for content validity by scholars with expertise in spectator sports―the F-1 Chinese Grand Prix in particular―before they were adopted for the current study. All the items were developed in English and translated into Chinese, and back-translation was employed based on Brislin’s suggestion (1990). The original scales in Korean were first translated into English and then re-translated into Chinese by a native Chinese researcher who is fluent in English. To ensure the accuracy and equivalence of the translation, the translated version was then converted back into English and in turn re-translated into Korean. This process ensured that there were no discrepancies between the two versions. Descriptive statistics for variables is presented in <Table 1>.

Data Analysis

The data were analyzed in SPSS version 20.0 for Windows. Exploratory factor analysis was conducted to ensure the validity of the current data set, and multiple regression analyses were performed to assess the effect of service quality on revisit intention and WOM.

Exploratory Factor Analysis

The kurtosis and skewness of all of the items were assessed, and no extreme value exceeding 3.0 was found (Kline, 2010). A principal component analysis (PCA) was conducted on the 26 items of the service quality scale with orthogonal rotation (varimax). The items that clustered on the same components suggested 6 sub-factors: promotion, staff, price, convenience, game experience, and facilities. Four items had factor loadings less than .40 or loaded incorrectly; however, these items were retained because prior studies have suggested that they are theoretically relevant to their respective constructs (Kwon et al., 2013; Ormiston et al., 1998). The Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO = .89, which is well above the acceptable limit of .5 (Field, 2009). Bartlett’s test of sphericity, χ² (325) = 5884.796, p < .001, indicated that correlations between items were sufficiently large for PCA. In addition, Cronbach’s alpha ranged from .69 to .87, indicating acceptable reliability given the values greater than .60 (Schuessler, 1971). The three items comprising revisit intention were combined to form a single index assessing the degree of revisit intention (α = .819). Similarly, the three items comprising WOM were combined to form a single index assessing degree of WOM (α = .839). The items of revisit intention and WOM were reviewed by five professionals in the field of sports and management to ensure the construct validity. Summary of exploratory factor analysis is presented in <Table 2>. In addition, interfactor correlation matrix is presented in <Table 3>.

Effect of Service Quality on Behavioral Intentions

The results of multiple regression indicated that service quality had a significant influence on behavioral intentions <Table 4>. Specifically, five of the six service quality attributes had a significant effect on revisit intention: convenience, facilities, price, game experience, and promotion. Approximately 26% of the variance in revisit intention was explained by these service quality attributes. In addition, four of the six service quality attributes had a significant effect on WOM: convenience, facilities, game experience, and staff. Approximately 41% of the variance in WOM was explained by these service quality attributes.