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With the application of mobile communication technologies such as 4G/5G, social media has been developing rapidly in the world. A few social networking platforms such as Facebook, Twitter and WeChat have received wide adoption among users. At the same time, e-commerce has become a popular channel for users to purchase products and services. A report indicated that about 79.7% of internet users (749 million) have conducted online shopping in China (CNNIC, 2020). Recently, e-commerce has been integrated with social media, which leads to the emergence of social commerce (Han et al., 2018). Compared to traditional e-commerce, social commerce can leverage the social networking relationship between users to create value for businesses (Wang et al., 2019). Realizing the great market potential, companies have begun to adopt social commerce model. For example, Facebook launched the F-commerce, which allows companies to create online stores in its platform. As one of the leading e-commerce companies in China, JD has cooperated with WeChat, which is the largest social networking platform. However, similar to e-commerce, social commerce transactions also involve risk and uncertainty, which includes seller uncertainty and product uncertainty (Bai et al., 2015). This may negatively affect users’ experience, which in turn leads to their low transaction intention. Companies need to understand the factors affecting user experience and take effective measures to facilitate his or her behaviour.
Previous research has examined social commerce user behaviour from multiple perspectives, such as trust (Cheng et al., 2019; Sharma et al., 2019; Wang and Herrando, 2019), social support (Molinillo et al., 2020; Tajvidi et al., 2021), and social interaction (Liu et al., 2016; Xiang et al., 2016; Wang and Yu, 2017). These factors are mainly related to cognitive beliefs. However, an individual user’s behaviour may also receive influence from emotional beliefs (Tsai and Bagozzi, 2014), such as flow, which reflects an optimal experience. Especially, we still have a very limited knowledge on the determinants of flow in social commerce. In other words, how to develop flow remains a question. This may undermine our understanding of social commerce user behaviour.
The purpose of this research is to identify the effect of flow experience on users’ social shopping intention. We integrated both perspectives of social support and network externality to investigate their effects on the flow. Social support reflects the informational and emotional interaction between users (Molinillo et al., 2020). It has been found to be a significant determinant of user behaviour in the social commerce context (Zhang and Benyoucef, 2016). Network externality reflects the added utility with the increase of user number (Lin and Bhattacherjee, 2008). As social commerce is based on social media, it may exert a significant network externality. Network externality has been examined in the context of social networking services (SNS) (Zhang et al., 2017; Zhu and Bao, 2018). We propose that a social commerce user’s experience may receive a dual influence from his or her peers (social support) and the platform (network externality). That is, a user’s experience is not only influenced by the informational and emotional support offered by other members, but also influenced by the externality utility obtained from the platform. To some extent, social support represents a social factor, whereas network externality represents a technological factor. By combining both social and technological perspectives, we can gain a complete understanding of social commerce users’ flow experience development.