Integrating event image, satisfaction, and behavioral intention: small-scale marathon event.

Koo, Sung Keun "SK" ; Byon, Kevin K. ; Baker, Thomas A., III 等

Introduction

The increasingly competitive marketplace, in which most major destinations offer first-rate attractions, accommodations, and service, has created numerous challenges for marketers. Moreover, the destinations themselves have faced additional potential crises caused by climate change and global economic slowdown (Bujosa & Rossello, 2013; Eugenio-Martin & Campos-Soria, 2014). However, hosting a sport event has recently become one of the best ways to differentiate a city or community from competing locations (Chalip, Green, & Hill, 2003; Chalip & McGuirty, 2004; Jago, Chalip, Brown, Mules, & Ali, 2003). The sport events come in all shapes and sizes, from the vast international scale of the Olympic Games to moderately-sized events such as a national championship to small-scale events on the local or regional level (Kaplanidou & Vogt, 2006). Regardless of the size, hosting a sport event generates valuable benefits, such as (a) creating destination awareness, (b) improving destination image, and (c) increasing future inbound travel (Dimanche, 2003). Moreover, Turco (1998) listed three main benefits to hosting a sport event: (a) providing local entertainment, (b) enhancing community pride, and (c) stimulating the host community's economy. Turco (1998) stated that economic benefit is the primary reason to host a sport event, for the outcome of the event is often the decisive factor in future resource allocation decisions.

One type of large-scale sport event is the mega event (e.g., the Olympic Games and the FIFA World Cup); these types of events have been found to generate significant economic impact on the various cities and countries involved (Lee & Taylor, 2005). Mega events are defined as short-term events that have long-term consequences (Roche, 1994), draw a significant number of domestic and international tourists, attract high media interest on an international scale, and generate significant amount of money through corporate sponsorships (Lee & Taylor, 2005). While mega events substantially contribute to marketing appeal and local economic development for a host community, Higham (1999) suggested that a small-scale event (e.g., marathon and Senior Games) can also yield benefits because they operate within an existing infrastructure, require a smaller budget, create a more manageable level of crowd congestion, and have high-impact regional effects on the community. Marathon running is one type of small-scale sport event that has grown tremendously during the past decade (Ridinger, Funk, Jordan, & Kaplanidou, 2012). Marathon running has grown in popularity since the 1970s, when it was more of a spectator sport. Today, however, the sport has become a popular leisure activity with benefits for participants that include goal achievement, improved health, affiliation, and improved self-esteem (Masters, Ogles, & Jolton, 1993). The positive benefits associated with marathon running help explain why the sport has grown in popularity. According to the Running USA's 2012 annual marathon report, marathons have played a role in the unprecedented upward trend line of running's second boom, and 2011 was another year of growth in U.S. marathons with an estimated record of 518,000 finishers, a 2.2% increase over 2010. Moreover, the launch of more than 35 new marathon events in 2010 brought the U.S. total to more than 625 from approximately 200 in 1985 (Helliker, 2011). The number of participants and marathon events has increased, demanding more effective marketing strategies not only to meet participants' needs, but also to maintain the popularity of the events themselves. Accordingly, marathon running events are a type of small-scale sport event that brings positive effects to host communities when effectively conducted and marketed.

Despite the positive effects and the prevalence of small-scale events, such as marathons, very few studies have identified the important determinants of post-decision behaviors, limiting the development of effective marketing strategies for small-scale event organizers. For example, event image has been found to be an important predictor of post-consumption variables, such as levels of satisfaction (Kaplanidou & Vogt, 2007) and behavioral intention (Kaplanidou & Gibson, 2012). In line with previous studies, new investigations in this area might reveal new relationships between possible antecedents (e.g., event image and satisfaction) that determine post-decision behaviors. Though satisfaction has been incorporated as either a consequence of event image (Kaplanidou & Vogt, 2007) or an antecedent of behavioral intention (Kaplanidou & Gibson, 2010), no empirical work has examined the mediating role of satisfaction in the relationship between event image and behavioral intention at a small-scale marathon event. Thus, the main purpose of this study was to investigate the hierarchical relationship among event image, satisfaction, and behavioral intention (i.e., intention to revisit and recommend the event to others) in the context of a small-scale marathon event. The specific objectives of the current study were (a) to examine the structural relationships among event image, satisfaction, and behavioral intention and (b) to investigate the mediating effect of satisfaction on the relationship between event image and behavioral intention. By understanding the relationships between behavioral intention and its determinants, as well as the mediating effect of satisfaction, researchers can establish a more comprehensive framework for identifying the specific aspects that influence behavioral intention at small-scale marathon events. From a marketing perspective, this study is important because it provides information to help event organizers build a more attractive event image and improve marketing strategies to maximize their use of resources when hosting a small-scale marathon event (e.g., hosting races of various distances and linking participants' emotions more closely to the event). In order to aid both scholars and practitioners, the following section provides a more detailed explanation of each variable and develops the hypotheses and the mediation model.

Literature Review

Event Image

Given that a destination hosts a sport event to attract spectators or participants (Hinch & Higham, 2001; Kaplanidou & Vogt, 2010), the concept of event image is similar to the concept of destination image (Hallmann, Kaplanidou, & Breuer, 2010). Regardless of the size of a sport event, event image depends in part on cognitive image (i.e., event organization and destination characteristics) and affective image (i.e., emotional and social aspects), both of which contribute to a holistic evaluation of the event (Baloglu & McCleary, 1999). Following Keller's (1993) theoretical framework, Gwinner (1997) defined event image as "the cumulative interpretation of meanings or associations attributed to events by consumers" (p. 147). Gwinner (1997) proposed a framework of three factors that might influence an individual's perception of a particular event: (a) event type (e.g., sports, music concert, and arts festival), (b) event characteristics (e.g., size, professional status, history, venue, and promotional appearance), and (c) individual factors (e.g., meanings associated with the event, strength of meanings, and past history of event).

The type of sport consumer (i.e., spectator or participant) is another factor that affects the formation of event image (Hallmann et al., 2010). Participants tend to link emotions more closely to physical and organizational aspects, whereas spectators tend to favor the social and historical aspects of a destination. Based on this distinction, Kaplanidou and Vogt (2006) defined event image as "the mental representations active sport tourism participants have about the organization, environment, physical activity, socialization, fulfillment and emotional involvement with the event" (p. 5). Utilizing the definition of event image, scholars have suggested that participants are likely to attach emotional, symbolic, and functional meanings to the sport event itself (Filo, Funk, O'Brien, Dwyer, & Fredline, 2008). Furthermore, Kaplanidou and Vogt (2007) developed the sporting event image (SEI) scale to assess perceived event image. The SEI was constructed as a 41-item semantic differential scale but was later condensed to 13 items for validity and reliability reasons. The revised SEI scale consists of 13 items: (a) unfulfilling/fulfilling, (b) stimulating/unstimulating, (c) poor/excellent, (d) sad/joyful, (e) healthy/unhealthy, (f) boring/exciting, (g) gloomy/cheerful, (h) valuable/worthless, (i) ugly/beautiful, (j) distressing/relaxing, (k) unadventurous/adventurous, (l) inspiring/uninspiring, and (m) unsupportive/supportive. One reverse item (i.e., stimulating/unstimulating) was included to avoid a favorable disposition toward the construct being measured with statements. After discriminant and convergent validity testing, the scale was used in the current study not only to capture the necessary elements of perceived event image, but also to examine their relationships with satisfaction and behavioral intention at small-scale marathon events.

Satisfaction

Competitive advantage in a competitive market-oriented industry depends on an ability to deliver high-quality services or products that satisfy consumers (Shemwell, Yavas, & Bilgin, 1998). Because satisfaction is assumed to be the post-evaluative judgment of recent experience (Kotler, 1997), satisfaction is defined as pleasure fulfillment through an overall evaluation of the service or product relative to the consumer's expectations (Oliver, 1999, 2010). Accordingly, satisfaction can be understood as a function of expectation and experience (Reisinger & Turner, 2012). That is, a consumer might be satisfied when an experience, given a set of expectations, results in feelings of gratification. On the other hand, when the event results in feelings of displeasure, the consumer might be dissatisfied. Satisfaction is an affective orientation toward all kinds of tangible and intangible products that consumers feel and experience (Oliver, 1999, 2010).

As satisfaction has been recognized as a crucial requisite in a competitive market-oriented industry, numerous studies have examined the antecedents and consequences of satisfaction in various post-consumption processes (e.g., Choi, Tsuji, Hutchinson, & Bouchet, 2011; Koo, Hardin, McClung, Jung, Cronin, Vorhees, & Bourdeau, 2009; Pantouvakis & Lymperopoulous, 2008). Previous studies have shown that satisfaction might vary depending on various factors, including perceived service quality, consumer moods, emotions, social interactions, and other experience-specific subjective factors (Pantouvakis & Lymperopoulous, 2008). More experienced consumers are also more likely to be satisfied with a service or product (Kim & Lough, 2007). In addition, evaluating experience has demonstrated that a satisfied consumer tends to be more committed to the company, service, or product than a less satisfied consumer (Cho, Lee, & Chon, 2004; Cronin, Brady, & Hult, 2000; Kelly & Turley, 2001; Tian-Cole, Crompton, & Wilson, 2002). More specifically, several post-consumption processes, including brand loyalty (Fornell, 1976), positive word-of-mouth (Richins, 1983), and repurchase intention (Oliver, 1980), have been found to be determined by satisfaction. Considering the role of satisfaction (Oliver, 1980), the current study measured specific contextual satisfaction (i.e., I truly enjoyed my visit to this marathon event) and overall satisfaction (i.e., I am satisfied with the overall experience) to examine the relationships among event image, satisfaction, and behavioral intention as well as the mediating role of satisfaction.

Behavioral Intention

Behavioral intention is defined as an individual's tendency to behave according to his or her feelings, knowledge, or evaluations of previous experiences (Spears & Singh, 2004). It can be categorized as favorable or unfavorable (Ladhari, 2009). Zeithaml, Berry, and Parasuraman (1996) suggested that favorable behavioral intention is associated with purchasing in the future, spreading positive word-of-mouth, paying a premium price, spending more money with the company, and remaining loyal. On the other hand, unfavorable behavioral intention includes leaving the company, spending less money with the company, spreading negative word-of-mouth, and taking legal action against the product or service provider. Furthermore, Wilson, Zeithaml, Bitner, and Gremler (2003) indicated that the economic benefit of favorable behavioral intention consists of reduced marketing and administrative costs, the ability to maintain margins without reducing prices, increased purchases over time, and reduced cost of attracting new consumers.

In the current study, behavioral intention was posited as a multidimensional outcome variable consisting of intention (a) to revisit the sport event in the future and (b) to spread positive word-of-mouth to prospective active participants, the two major components of customer loyalty. Because customer loyalty is crucial to long-term visibility and sustainability (Chen & Chen, 2010), and the cost of attracting new customers can be as much as five times greater than the cost of retaining customers (Reichheld, 1996), maintaining customer loyalty with a stream of profitability and investigating possible variables that could influence behavioral intention are important tasks. Therefore, the current study investigated event image and satisfaction, which could influence and interact with the behavioral intention to revisit a small-scale marathon event and recommend it to prospective participants (Boulding, Kalra, Staelin, & Zeithaml, 1993).

Hypothesis Development

In the past few decades, researchers have studied event image in terms of their own interests, especially event choice process and consequent behaviors (Kaplanidou, 2009; Kaplanidou & Vogt, 2007; Xing & Chalip, 2006). Previous studies on sport tourism have focused on the way event image and destination image can work together to affect behavioral intention (Jago et al., 2003; Xing & Chalip, 2006). For example, Xing and Chalip (2006) found that destination image influenced behavioral intention when an event image present in a destination advertisement matched the activity characteristics of said destination image. Although little attention has been paid to event image itself and its consequent variables, previous image-related studies have confirmed that event image has a positive influence on levels of satisfaction with a bicycling tour event (Kaplanidou & Vogt, 2007). In addition, Kaplanidou and Gibson (2012) found that event image becomes important in the formation of behavioral intention when youth sport events are viewed as an acceptable pastime and activity for the family and friends. Consequently, a more positive event image not only might show a higher level of event image strength compared to competing events, but also might correspond to higher levels of satisfaction and behavioral intention for a small-scale marathon event. Accordingly, the review of the event image literature led to the following hypotheses:

H1a: Event image associated with a marathon event will positively influence satisfaction with marathon participation.

H1b: Event image associated with a marathon event will positively influence behavioral intention toward marathon participation.

As satisfaction is an overall affective response to a service or product, numerous studies have explored the relationship between satisfaction and behavioral intention (Cho et al., 2004; Cronin et al., 2000; Yoo, Cho, & Chon, 2003). These studies found that satisfaction positively correlated with behavioral intention, including repurchase intention and positive word-of-mouth. Similar findings are also identified in the sport event context (Wakefield & Blodgett, 1996; Yoon & Uysal, 2005). For example, Wakefield and Blodgett (1996) found that satisfaction with the service environment had a significant effect on behavioral intention to revisit football and baseball venues. In the same way, several studies have indicated that satisfaction was a strong indicator of intention to revisit and to spread positive word-of-mouth, which are primary indicators of customer loyalty (Yoon & Uysal, 2005; Yoshida & James, 2010). Consequently, satisfied participants are more likely to return to the same event and share their positive experience with friends and relatives. Thus, the findings of previous studies led to the following hypothesis:

H2: Satisfaction with the marathon participation will positively influence behavioral intention toward marathon participation.

Mediating Effect of Satisfaction

Studies have shown that the link between image and customer loyalty is mediated by evaluative judgments such as satisfaction (Bloemer, Du Ruyter, & Peeters, 1998). Considering this general relationship, Chi and Qu (2008) established the following sequence: image [right arrow] satisfaction [right arrow] behavioral intention. Though satisfaction has been incorporated as either a consequence of event image or an antecedent of behavioral intention (Kaplanidou & Vogt, 2007; Kaplanidou & Gibson, 2010), no empirical work has examined the mediating role of satisfaction between event image and behavioral intention at a small-scale marathon event. While event image contains cognitive and affective components that contribute to the holistic evaluation of an event (Baloglu & McCleary, 1999), the mediation model was tested not only to fill these voids but also to generate new knowledge about active participants' perceptions of a small-scale marathon event. Consistent with the role of satisfaction as well as the hypothesized relationships, the mediation model depicted that event image would have a direct effect on behavioral intention and an indirect effect through satisfaction as well. In addition, this model illustrated that satisfaction would have a positive effect on behavioral intention.

Method

Participants

As this study attempted to offer important implications that can be used to develop marketing strategies at a small-scale marathon event, data were collected from participants at small-scale marathon events held in southeastern cities in the United States: (a) the Mercedes-Benz Marathon Event in Birmingham, AL, and (b) the Publix Marathon Event in Atlanta, GA. In order to measure participant satisfaction specially, our study included a screening question to distinguish participants from spectators at each event. Only respondents who indicated that they had participated in the marathon event were included. A convenience sample was drawn, and the active participants were intercepted to fill in the questionnaire after the event. A total number of 322 questionnaires were collected from the marathon events. Twenty-five questionnaires were eliminated because they were incomplete or incorrectly filled in. Consequently, 297 valid questionnaires were accepted for subsequent analyses.

A list of the respondents' demographics is provided in Table 1. The demographic profile of the respondents indicated that the average age was 36. In terms of gender, 49.5% were male and 50.5% were female. Ethnicity was predominantly Caucasian (64.6%), followed by African American (18.5%). The majority of respondents were highly educated; 69.0% held a college degree, and 20.5% held a graduate degree. With regard to annual income, 35.4% of the respondents earned an annual income of $50,000-$75,000, followed by $75,000$100,000 (20.5%), and $25,000-$50,000 (17.8%).

Instruments

Based on the literature review, a questionnaire was developed that consisted of four sections: (a) event image, (b) satisfaction, (c) behavioral intention, and (d) socio-demographics. The SEI scale, which consists of 13 five-point semantic differential scale-type items, was used to measure event image (Kaplanidou & Vogt, 2007). Satisfaction was measured using two items adapted from Oliver (1980). The items were modified as follows: "I truly enjoyed my visit to this marathon event" and "I am satisfied with the overall experience." These items were measured on a 5-point Likert scale ranging from 1 ("strongly disagree") to 5 ("strongly agree"). Behavioral intention was measured using two items: (a) likelihood of revisiting the event and (b) willingness to recommend the event to significant others (Boulding et al., 1993). These items were measured on a 5-point Likert scale ranging from 1 ("strongly disagree") to 5 ("strongly agree"). Socio-demographic information gathered in the study included age, gender, ethnicity, education, and income level. Following the development of the questionnaire, panel experts consisting of sport management and marketing professors reviewed it for content validity. They were asked to assess the content relevance, representativeness, and clarity of the items. They also provided suggestions for changing words and phrases to increase clarity. Acting on the feedback derived from the panel experts, minor wording changes were made.

Data Analysis

Procedures from the Statistical Package for the Social Science (SPSS 19.0) were used to calculate descriptive statistics, central tendency (e.g., mean), measures of variability (e.g., standard deviation), and data normality (e.g., skewness and kurtosis). A Confirmatory Factor Analysis (CFA) was conducted on the proposed model to ensure the measurement model's psychometric properties. Various model fit indices were used, including standardized root mean square residual (SRMR), root mean square error of approximation (RMSEA), Tucker-Lewis index (TLI), and comparative fit index (CFI). Additionally, convergent validity was assessed in terms of factor loadings in the measurement model. Furthermore, discriminant validity was assessed by comparing squared correlations among the constructs. Lastly, Cronbach's alpha, Composite Reliability (CR), and Average Variance Extracted (AVE) were calculated to assess inter-item reliability of the three constructs (Hair, Anderson, Tatham, & Black, 1998).

Upon the testing the measurement model, regression analyses were employed to examine the impact of event image and satisfaction on behavioral intention as well as the impact of event image on satisfaction. Following Baron and Kenny's (1986) guidelines, a series of hierarchical regressions were also conducted to test the mediating role of satisfaction in the relationship between event image and behavioral intention. A variable serves as a mediator when it fulfills the following conditions: (a) the purported predictor (i.e., event image) is related to the mediator (i.e., satisfaction) and the criterion variable (i.e., behavioral intention), (b) the mediator has a significant unique effect on the criterion, and (c) upon the addition of the mediator to the model, the magnitude of the predictor on the criterion becomes either insignificant (fully mediating) or reduced (partially mediating). Finally, the Sobel test was conducted to examine the significance of the indirect effect (Sobel, 1982).

Results

Descriptive Statistics

Mean scores as well as standard deviations for event image, satisfaction, and behavioral intention are shown in Table 2. The mean scores of the event image items ranged from 3.98 to 4.41 on the 5-point semantic differential scale. These scores suggest that most respondents generally held a positive image of the Mercedes-Benz Marathon Event and the Publix Marathon Event. The mean scores of the satisfaction items ranged from 4.42 to 4.47, indicating that most respondents felt a high level of satisfaction with the two marathon events. The mean scores of the behavioral intention items ranged from 4.43 to 4.47, suggesting that most respondents had positive behavioral intention toward future event participation.

Psychometric Properties of the Measurement Model

CFA was conducted on the proposed model to ensure psychometric properties. The results indicate a good fit of the hypothesized model to the data (= 586.915; df = 244; SRMR= .053; RMSEA = .069; TLI = .913; & CFI = .923). In addition, convergent validity was assessed in terms of factor loadings in the measurement model. Convergent validity is evidenced when factor loadings are equal to or greater than .50 (Hair et al., 1998). As shown in Table 3, factor loadings for each item ranged from .64 to .87, indicating that convergent validity was established. Furthermore, comparison of squared correlations among the constructs was used to measure discriminate validity, which should be less than .85 (Kline, 2010). The estimated correlations among the exogenous latent constructs ranged from .51 to .82, confirming discriminant validity. Lastly, Cronbach's alpha, CR, and AVE were calculated to assess the reliability of the three instruments. For items to be reliable, Cronbach's alpha and CR should be greater than the suggested cut-off value of .70, and AVE should be greater than the recommended cut-off value of .50 (Fornell & Larcker, 1981). As presented in Table 3, the values for Cronbach's alpha and CR were above .70, and the values for AVE were above .50. Therefore, the psychometric properties of the measurement model were good.

Hypothesis Testing

Regression analyses were conducted to examine the impact of event image and satisfaction on behavioral intention as well as the impact of event image on satisfaction. In detail, hypothesis 1a predicted that event image would positively influence satisfaction. The results indicate that event image had a significant influence on satisfaction ([beta] = .55, p < .05), supporting hypothesis 1a. Hypothesis 1b posited that event image would positively influence behavioral intention. The results also show that the influence of event image on behavioral intention was significant ([beta] = .54, p < .05), supporting hypothesis 1b. Finally, hypothesis 2 predicted that satisfaction would positively influence behavioral intention. Satisfaction had a significant effect on behavioral intention ([beta] = .82, p < .05), supporting hypothesis 2. The results of these regression analyses are presented in Table 4.

Baron and Kenny's (1986) guidelines were used in this study for testing the mediating role of satisfaction in the relationship between event image and behavioral intention. The first step showed that the influence of event image on both satisfaction ([beta] = .55, p < .05) and behavioral intention ([beta] = .54, p < .05) was significant, and the second step indicated that satisfaction was significantly related to behavioral intention ([beta] = .82, p < .05). The third step revealed that when satisfaction was controlled, the influence of event image on behavioral intention was still significant ([beta] = .12, p < .05) but that the magnitude of the beta coefficient was reduced, indicating that satisfaction partially mediated the relationship between event image and behavioral intention for participants at a small-scale marathon event (see Figure 1). In addition, the z-value provided by the Sobel test was 2.44 (p < .05), indicating that the indirect effect of event image on behavioral intention through satisfaction was statistically significant.

Discussion

This study focused on investigating the hierarchical relationship among event image, satisfaction, and behavioral intention (i.e., intention to revisit and recommend the event to others) in the context of a small-scale marathon event. The results offered support for the statistically significant relationship between event image and behavioral intention. That is, participants with positive and favorable event image were likely to have positive future behavioral intention toward a small-scale marathon event. This finding is consistent with previous findings that event image has a positive influence on revisiting and recommending an event (Kaplanidou & Gibson, 2012). In addition, with reference to the relationship between satisfaction and behavioral intention, the regression analysis also indicates that greater satisfaction with the marathon event made positive future behavioral intention more likely. This result is also consistent with previous studies that recognized satisfaction as a good predictor of behavioral intention (Bigne, Sanchez, & Sanchez, 2001; Chen & Tsai, 2007). Following Baron and Kenny's (1986) guidelines, the current study found that satisfaction partially mediated the relationship between event image and behavioral intention at a small-scale marathon event. Positive event image related to both satisfaction and positive future behavioral intention for participations of the small-scale marathon events. Previous studies have indicated that a more positive image of a destination corresponded to higher levels of satisfaction, which, in turn, determined behavioral intention (Chi & Qu, 2008). In line with those findings, the current study provides additional support through a series of hierarchical regressions. In other words, event image was found to be a determinant of satisfaction and behavioral intention.

Marketing Implications

The findings of this study provide a number of insights and important implications for small-scale marathon event organizers interested in developing marketing strategies based on the identification of key elements of participants' decision making. First, marathon event organizers should consider building a positive event image and maintaining that image. For example, marathon event organizers should provide the participants with positive experiences that enhance the organizational, environmental, emotional, social fulfillment, and physical activity aspects of the event (Kaplanidou & Vogt, 2006). Event image appears to be a direct antecedent of satisfaction, as well as a major influence on behavioral intention, even without the mediation of satisfaction. This finding supports the position that marathon event organizers should develop and pursue an event image-development agenda by focusing on event image attributes that influence satisfaction and behavioral intention. Second, enhancing satisfaction should be considered a strategic investment for event organizers. The general view is that if participants are satisfied, they will have positive behavioral intention (i.e., engaging in positive word-of-mouth and returning to the event site) in the future (Kaplanidou & Gibson, 2010). This study also provides empirical evidence supporting the notion that satisfaction directly affects behavioral intention at a small-scale marathon event. Furthermore, based on the finding that completing a marathon race can enhance event satisfaction, marathon organizers should consider hosting races of various distances (e.g., 5K and half marathon) to draw participants with different levels of confidence and experience so that a greater number of participants will be able to complete their races. Lastly, as satisfaction was found to play an important mediating role in the relationship between event image and behavioral intention, improving event image with satisfaction could maximize positive outcomes in terms of participants' behavioral intention. Therefore, marathon event organizers should develop a strategy for enhancing satisfaction through event image (i.e., linking participants' emotions more closely to the event).

[FIGURE 1 OMITTED]

Limitations and Suggestions for Future Research

As with all research investigations, several limitations should be addressed. First, the data for this study were collected at only two small-scale marathon events held in the southeast region of the United States. This narrow scope possibly means that the results are not generalizable to all participants of small-scale marathon events in other parts of the country or the world. Additional data collection at small-scale marathon events in other locations would increase the external validity of the tested model. A second limitation is that even though event image explained a good amount of satisfaction and behavioral intention at a small-scale marathon event, additional images, such as sponsor image (e.g., Mercedes-Benz and Publix) and destination image, might give further insight into the outcome variables. Thus, future research might include those images to uncover additional relationships with the outcome variables. Thirdly, although event image in this study was the only antecedent of satisfaction and behavioral intention, additional factors, such as perceived value, could influence and interact with those variables. Because participants might weigh the costs against the perceived benefits of their experience at a small-scale marathon event, re-conceptualizing the proposed model by including perceived value might enhance our understanding of how event image and perceived value interact with satisfaction to influence behavioral intention (i.e., revisit and word-of-mouth) in the context of small-scale marathon event. Fourth, testing the moderating effect of a variable such as frequency of participation (i.e., first-time vs. return participants) might also allow researchers and event organizers to better understand event consumption behaviors toward small-scale marathon event. Lastly, future studies could use structural equation modeling (SEM) to estimate a conceptual model, a useful method when the constructs are fully latent variables measured with multiple indicators (Kline, 2010), for SEM can take into consideration the measurement error variance associated with the indicators that represent the latent variables (Kline, 2010).

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Sung Keun (SK) Koo, MS, is a doctoral student of sport management in the Department of Kinesiology at the University of Georgia. His research interests include event sport marketing.

Kevin K. Byon, PhD, is an associate professor of sport management in the Department of Kinesiology at the University of Georgia. His research interests include sport marketing and sport consumer behavior.

Thomas A. Baker III, JD, PhD, is an associate professor of sport management in the Department of Kinesiology at the University of Georgia. His research interests include sport law and terrorism and sport facilities.

Table 1 Demographic Characteristics

Variables              Category       Frequency

Age                                     36.29

Gender                   Male         146 (49.2)
                        Female        150 (50.5)

Ethnicity             Caucasian       192 (64.6)
                   African-American   55 (18.5)
                       Hispanic        16 (5.4)
                        Asian         30 (10.1)
                   Pacific Islander     1 (.3)
                        Other           2 (.7)

Household Income    Less than $25K     29 (9.8)
                     $25K ~ $50K      53 (17.8)
                     $50K ~ $75K      105 (35.4)
                     $75K ~ $100K     61 (20.5)
                    $100K ~ $150K      23 (7.7)
                   More than $150K     17 (5.7)

Education            High School       29 (9.8)
                    College Degree    205 (69.0)
                   Graduate School    61 (20.5)

Table 2

Descriptive Statistics for Event Image, Satisfaction,
and Behavioral Intention

Factor         Item                                M     SD

Event Image
               Stimulating/Unstimulating          4.01   .89
               Poor/Excellent                     4.21   .82
               Sad/Joyful                         4.31   .78
               Healthy/Unhealthy                  4.41   .86
               Gloomy/Cheerful                    4.25   .85
               Distressing/Relaxing               3.98   .93
               Inspiring/Uninspiring              4.01   .91
               Unsupportive/Supportive            4.13   .84
Satisfaction
               I truly enjoyed my visit to this   4.47   .63
                 marathon event
               I am satisfied with the overall    4.42   .68
                 experience
Behavioral
Intention
               I am likely to revisit this        4.43   .72
                 marathon event
               I am likely to recommend this      4.47   .69
                 marathon event

Factor         Item                               Skewness   Kurtosis

Event Image
               Stimulating/Unstimulating           -1.13       1.71
               Poor/Excellent                       -.76       -.18
               Sad/Joyful                           -.69       -.73
               Healthy/Unhealthy                   -1.98       4.68
               Gloomy/Cheerful                     -1.02       .73
               Distressing/Relaxing                 -.71       .25
               Inspiring/Uninspiring                -.92       .66
               Unsupportive/Supportive              -.78       .40
Satisfaction
               I truly enjoyed my visit to this    -1.18       2.65
                 marathon event
               I am satisfied with the overall     -1.01       1.12
                 experience
Behavioral
Intention
               I am likely to revisit this         -1.19       1.40
                 marathon event
               I am likely to recommend this       -1.25       1.66
                 marathon event

Table 3

Factor Loadings, Cronbach's Alpha, Composite Reliability,
and Average Extracted Variance for Event Image, Satisfaction,
and Behavioral Intention

Factor         Item                          [lambda]   [alpha]

Event Image                                              .896
               Stimulating/Unstimulating       .660
               Poor/Excellent                  .642
               Sad/Joyful                      .873
               Healthy/Unhealthy               .874
               Gloomy/Cheerful                 .825
               Distressing/Relaxing            .815
               Inspiring/Uninspiring           .817
               Unsupportive/Supportive         .688
Satisfaction                                             .866
               I truly enjoyed my visit to     .734
                 this sport event.
               I am satisfied with the         .770
                 overall experience.
Behavioral                                               .901
Intention
               I am likely to revisit this     .874
                 marathon event.
               I am likely to recommend        .746
                 this marathon event.

Factor         Item                           CR    AVE

Event Image                                  .924   .607
               Stimulating/Unstimulating
               Poor/Excellent
               Sad/Joyful
               Healthy/Unhealthy
               Gloomy/Cheerful
               Distressing/Relaxing
               Inspiring/Uninspiring
               Unsupportive/Supportive
Satisfaction                                 .771   .529
               I truly enjoyed my visit to
                 this sport event.
               I am satisfied with the
                 overall experience.
Behavioral                                   .889   .668
Intention
               I am likely to revisit this
                 marathon event.
               I am likely to recommend
                 this marathon event.

Table 4

Regression Analyses (N = 297)

Independent    df   [R.sup.2]   [DELTA][R.sup.2]      F
Variable

Dependent Variable: Behavioral Intention

Event Image    1      .298           .295          125.007
Satisfaction   1      .680           .679          626.938

Dependent Variable: Satisfaction

Event Image    1      .313           .311          134.337

Independent    [beta]     Sig.
Variable

Dependent Variable: Behavioral Intention

Event Image    .546     .000 ***
Satisfaction   .825     .000 ***

Dependent Variable: Satisfaction

Event Image    .559     .000 ***

Note. *** p < .001

Table 5
Sobel Test (N = 297)

Path                                      Z     Probability Level

Event Image [right arrow] Satisfaction   2.44        0.014 *
  [right arrow] Behavioral Intention

Note. * p< .05