The purpose of this study was to propose and test a conceptual model of online sport consumption motivation and concerns when using the Internet for sport information and shopping. The proposed model is based on current conceptualization of motivation and concerns when using the Internet. The proposed model consists of five types of motivation (i.e., convenience, information, diversion, socialization, and economic) and four types of concern (i.e., security and privacy, delivery, product quality, and customer service). To test this model, the scale of motivation for online sport consumption was developed. A structural equation model test with a convenience sample of 222 sports participants supported the conceptualization of motivation and concerns. Motivation positively influenced sport fans’ actual usage of sport-related Web sites, but no significant path coefficient was found from concerns to motivation and actual usage. Given these results, implications for future research and practice are discussed.

We report 3 experiments examining the effects of positive versus negative valence and perceptual load in determining attention capture by irrelevant emotional distractors. Participants performed a letter search task searching for 1 of 2 target letters (X or N) in conditions of either low perceptual load (circular nontarget letters) or high perceptual load (angular nontarget letters that are similar to the target letters). On 25% of the trials an irrelevant emotional distractor was presented at the display center and participants were instructed to ignore it. The distractor stimulus was either positive or negative and was selected from 3 different classes: IAPS pictures of erotica or mutilated bodies (Experiment 1), happy or angry faces (Experiment 2), and faces associated with gain or loss in a prior value-learning phase involving a betting game (Experiment 3). The results showed a consistent pattern of interaction of load and valence across the 3 experiments. Irrelevant emotional distractors produced interference effects on search reaction time (RT) in conditions of low load, with no difference between negative and positive valence. High perceptual load, however, consistently reduced interference from the negative-valence distractors, but had no effect on the positive-valence distractors. As these results were consistently found across 3 different categories of emotional distractors, they suggest the general conclusion that attentional capture by irrelevant emotional distractors depends on both their valence and the level of perceptual load in the task and highlight the special status of distractors associated with pleasure.

The Internet website has become an effective marketing vehicle for sport organizations. The purpose of this study was to examine theoretical relationships between key variables of online sport consumption behavior such as sport consumers’ perceptions of sport website quality, satisfaction, and behavioral loyalty to the websites. In addition, the mediating effect of e-satisfaction between website quality and e-loyalty was examined. The results of data analyses using structural equation model tests revealed that loyalty to a sport team’s website was more likely to occur as sport fans developed positive perceptions and satisfaction with the website. The results also suggested that consumer e-satisfaction is an important mediating variable between sport website quality and e-loyalty.

This study empirically tested the Sport Website Acceptance Model (SWAM), proposed by Hur, Ko and Claussen (2007). The SWAM added Perceived Enjoyment (Davis et al, 1992) and Perceived Trustworthiness (Belanger et al, 2002) to the two factors Perceived Ease of Use and Perceived Usefulness used in the Technology Acceptance Model (TAM) (Davis, 1989). This study proposes a competing model to the original SWAM and compares this by incorporating two additional constructs, Sport Involvement (Shank & Beasley, 1998) and Psychological Commitment to a Team (Mahony et al, 2000). Structural equation modeling analyses revealed acceptable model fits, both in the original SWAM and in the competing model. Subsequent analyses led the authors to conclude that the competing model was the better version of the SWAM.