With the advances in digital and social media technologies, sportswear and athletic shoe brands have provided more technology-based services to their consumers (Do et al., 2015). Accordingly, the importance of direct-to-consumer (DTC) sales has been increased, especially DTC sales through social media and mobile technologies. In the case of Nike, the relative contribution of DTC sales has been increased over the last few years in comparison to the sales to wholesalers while sales to wholesalers are still the primary revenue source (Soni, 2014). Despite the increasing importance of DTC sales, Nike is lagging in the market in terms of the ratio of DTC revenue to total revenue as opposed to its competitors (Soni, 2014). In response, Nike has implemented various DTC initiatives using digital and social media to facilitate demand creation and maintain market dominance (Guard, 2013; Heitner, 2016; Soni, 2014). In an effort to increase the DTC revenues, Nike introduced the new Nike+ app in 2016; however, the new app has been not well received by the public due to some functionality and gamification issues (Welch, 2016). Given the importance of the mobile apps’ forefront role for any sports brand, it is critical to understand what influence the adoption and use of the brand apps in order to increase the user satisfaction level and adoption. Thus, the current study examined factors influencing consumers’ use of a sports brand app using the modified technology acceptance model (Davis et al., 1992; Ha et al., 2015; Kim et al., 2017). Data were collected from 261 Nike+ Run Club app users using convenience sampling method. Of 216 app users, 133 respondents (51%) were female 129 were male (49%). About 64.8% were between the ages of 20 and 39 years and 35.2% were aged over 40 years. All respondents had previous experience with the Nike+ app. The questionnaire included the scales that measure perceived enjoyment, perceived ease of use, perceived usefulness, intention to use, and actual usage frequency as well as personal information. Harman’s single factor test was conducted to examine a possibility of the common method variance (MacKenzie & Podsakoff, 2012). Data were primarily analyzed using partial least squares structural equation modeling (PLS-SEM) and multi-group analysis (PLS-MGA). PLS algorithm procedures were performed to examine the hypothesized relationships in the research model (Ringle et al., 2015). The level of enjoyment had a significant positive effect on perceived ease of use (beta = .58, t = 11.94) while perceived ease of use positively affected perceived usefulness (beta = .58, t = 9.81). Behavioral intention was significantly influenced by perceived enjoyment (beta = .45, t = 7.46), followed by perceived usefulness (beta = .32, t = 3.64), and perceived ease of use (beta = .16, t = 2.07). As expected, behavioral intention positively affected actual behavior (beta = .31, t = 5.90). PLS-MGA was conducted to explore the differences between three age groups; 20s (n = 78), 30s (n = 91) and over 40 (n = 92), in regard to the use of a sports brand app. The relationship between variables was stronger with younger age groups, except the relationship between perceived enjoyment and behavioral intention. The greater the age, the greater the influence of perceived enjoyment on behavioral intention. However, only the path from perceived ease of use to behavioral intention was significantly different between the 20s and above 40 groups. The present study provides evidence supporting the efficacy of the modified TAM for predicting behavioral intention and actual use in the context of a sports brand app. In general, results from the current study suggest that perceived enjoyment is a more powerful predictor than perceived ease of use and perceived usefulness. In this regard, the concept of gamification should be tactically applied when developing and improving a sports brand app in order to create engaging experience with enjoyment (Hofacker et al., 2016; Zichermann & Cunningham, 2011). Also, given that perceived usefulness is greatly influenced by confirmation of expectations, the sports brand app provider should conduct a more thorough market research to understand what is expected by app users and ways to meet their expectations (Yoon & Rolland, 2015). In addition, the current study found some evidences of age-related differences in the adoption and use of a sports brand app (Ha et al., 2015). More detailed results and discussion will be presented at the conference.