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With the rapid development of mobile applications worldwide in recent years, using mobile applications has become popular in users’ daily life (Hajiheydari & Ashkani, 2018; Sun et al., 2017). However, the numbers of monthly active users of mobile fitness apps is lower than that of other apps (e.g., instant message apps-Wechat). For example, the numbers of users of Yuedongquan and Keep, the top two fitness apps in China, were 10.475 million and 10.213 million in March, 2018, respectively, compared with WeChat, which had 905.925 million users (Askci, 2018). In fact, like the other mobile applications used by large-scale users, fitness apps provide enough functions for users’ health and fitness (e.g., body shaping and muscle building). Moreover, mobile fitness is a better way for users to work out at suitable locations and times without needing to go to fitness centers. Therefore, this phenomenon attracts the authors’ attention.
Sufficient research in CU supports the point that CU is important for the long-term development of information systems (Bhattacherjee, 2001; Hsiao, Chang, & Tang, 2016). Some studies showed that perceived usefulness (PU) regarding information system is an important determinant of CU (Bhattacherjee, 2001; Dehghani, 2018). In addition, stimulus-organic-response (S-O-R) theory explains how stimuli act on an organism, which in turn causes a particular behavior (Donovan & Rossiter, 1982). Studies on S-O-R clearly reveal the impact process of a stimulus on an individual’s behavior (Eroglu, Machleit, & Davis, 2001; Eroglu, Machleit, & Davis, 2003). However, studies seldom focus on how PU influences CU based on the S-O-R model in CU. In the mobile fitness context, fitness apps provide numerous functions that can be regarded as potential stimulus sources, and only the functions that users have perceived usefulness can be the real stimulus for fitness apps users (Lin & Hu, 2006). Therefore, the authors will consider PU as the stimulus for fitness apps users and the behavior of continuance usage of fitness apps (CUFA) as the response based on the S-O-R model to explore the influence mechanism of PU on CUFA. In this study, PU refers to the prospective user’s subjective probability that using fitness apps will increase his or her health and fitness benefit (Davis, Bagozzii, & Warshaw, 1989). CUFA refers to the users’ continued use of fitness apps for a period after adoption (Limayem & Cheung, 2008; Limayem, Hirt, & Cheung, 2007).
To conduct this study, the authors introduce satisfaction and attitude-based loyalty as organic to depict the users’ internal states after they are stimulated based on the S-O-R model. “Satisfaction is viewed as the key to building and retaining a loyal base of long-term consumers,” which underscores a psychological or affective state in CU (Bhattacherjee, 2001). Attitude-based loyalty can be used to depict the psychological meaning of loyalty, such as preference or intention of repurchasing (McMullan & Gilmore, 2008; Oliver, 1999). Some studies closely link user satisfaction and loyalty (Chiua, Linb, Sunc, & Hsuc, 2009; Hew, Lee, Ooi, & Lin, 2016). In this study, satisfaction is operationally defined as the degree of user affect with (feelings about) fitness apps use (Bhattacherjee, 2001). Attitude-based loyalty is operationally defined as user intention or preference regarding fitness apps use (Ozturk, Bilgihan, Nusair, & Okumus, 2016).