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Top1. Introduction
With the rapid growth of the Internet, companies have invested large amounts of money to develop online platforms for users. Although traditional sales channels have not disappeared, e-commerce has become an alternative. The company provides more online services, including more product information, customized services, competitive prices, and fast delivery. Therefore, the market for online shopping has also increased annually. In 2022, the Asian e-commerce market will exceed USD$ 2 trillion, and user penetration will be 57.1% (Statista, 2021). According to MOEA statistics, Taiwan’s e-commerce market is approximately USD$ 27.9 billion in 2020 (Department of Statistics, 2022). The number of young shoppers has increased, and they prefer to shop online.
Online shopping refers to the process of purchasing products or services on the Internet and eliminating the need for customers to satisfy their needs through face-to-face services (Li & Zhang, 2002). Research exploring online shopping has continued to grow due to the boom in online sales. The success of online platforms means that consumers are willing to adopt new ways of shopping and continue to use them (Bhattacherjee 2001a). In the past two years, the world has been affected by the pandemic, and consumers are less willing to shop via physical channels, and such shopping has been restricted (Alhaimer, 2021; Grashuis et al., 2020). Research on online shopping adoption often uses the technology acceptance model (TAM) to discuss the determinants of users' decisions (Agag & El-Masry, 2016). The TAM is mainly about technology adoption in the workplace rather than personal use (Shang & Wu, 2017). The model has been shown to have significant explanatory power in some studies (Shang & Wu, 2017) and provides information of initially adoption by the users (Gefen et al., 2003). Attitude is an antecedent that affects intention. Therefore, researchers have suggested adding other models to understand users’ intention (Shah et al., 2021) .
Previous studies have combined the TAM and the expectation confirmation model (ECM) in online shopping studies (Hong et al., 2006; Shang & Wu, 2017). ECM is used to analyze users’ continued use intention by individual factors (Oliver, 1980), combined with other models for better explanatory power. Consumers' expectations and satisfaction affect their willingness and likelihood of continuing to use or repurchase (Bhattacherjee, 2001a, 2001b). ECM refers to users having fixed expectations about a product or service before using it, and then having a new understanding of the performance of the product or service after the experience (Shah et al., 2021). The users compared the experience performance and inherent expectations, and the results will affect their satisfaction and, in turn, their willingness to reuse or purchase. This feature complements our understanding of continuous intention (CI). Both Perceived usefulness (PU) and satisfaction with the ECM may be affected by external factors (Venkatesh & Bala, 2008). PU stands for cognitive belief after acceptance (Bhattacharjee 2001b). Satisfaction is an important factor that affects CI (Bhattacherjee 2001a, 2001b). Furthermore, the user's continued use represents loyalty, which is critical for business success. CI has a significant effect on continued use behavior (Armitage & Conner, 2001).TAM can understand the initial motivation of users, while ECM can explain CI, which is also an influential factor of loyalty.