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Top1. Introduction
Information cascades are the scenario “when it is optimal for an individual, having observed the actions of those ahead of him, to follow the behavior of the preceding individual without regard to his own information.” (Bikhchandani et al., 1992), which can affect product adoption (Duan et al., 2009, Park et al., 2019) and sales (Liu et al., 2016, Liu et al., 2020). The online shopping platforms provide an ideal environment for the occurrence of information cascades (Liu et al., 2016; Simonsohn & Ariely, 2004). On the one hand, different from conventional environment of retail face to face, where consumers can touch products and consult salespeople, transactions take place in an online shopping platform that lays a condition of incomplete information (Khatwani and Srivastava, 2018; Sunder et al., 2019). Moreover, with the rapid development of e-commerce, as online retailers take advantage of virtually unlimited shelf space, competing products’ number in every product type grows in an exponential manner. For online shoppers, they usually find themselves without the time and knowledge to do the optimal purchase decision-making, often from dozens or even hundreds of completing products (Ding and Li, 2019). For another, a lot of online shopping platforms offer a lot of information about the choices and product popularity of other online customers. For example, Amazon.com provides a list of bestsellers and posts the sales ranking for each product.
Previous studies have confirmed the effect exerted by information cascades on online purchase behavior (Liu et al., 2016; Simonsohn & Ariely, 2004). However, prior studies focus on information cascades on the online shopping platform in a particular country, such as eBay.com in the United States (Simonsohn & Ariely, 2004) and Tmall.com in China (Liu et al., 2016). In fact, many brand retailers have entered electronic commerce platforms in different countries to sell online. For example, as a sportswear brand, ASICS has online stores on Tmall.com in China, as well as on eBay.com in the United States. Moreover, cross-border electronic commerce is rapidly developing globally. According to iiMedia Research, the global B2C cross-border electronic commerce transaction volume reached US$95.5 billion in 2019, up 27.5% year-on-year, and the global cross-border online shopping penetration rate reached 51.2% (iiMedia Research, 2019). However, few studies have compared the impact of information cascades in electronic commerce markets in different countries. In fact, consumers in different countries may have different cultural orientations (Deufel et al., 2019; Luo et al., 2014; Wang et al., 2019). The influence of customers’ cultural orientation on their cognitions and behaviors has been confirmed by a great many of studies (Deufel et al., 2019; Luo et al., 2014; Moon et al., 2008; Shiu et al., 2015; Wang et al., 2019). Although some recent literature has analyzed the moderating effects of cultural orientation on word-of-mouth behavior (Lee and Choi, 2019), social media usage (Hu et al., 2020), and diffusion of innovations (Pettifor et al., 2017) from the perspective of social impact, there is no research on consumer behavior combined with information cascades and cultural orientation. Due to the important impact of information cascades on online purchase behaviors, online merchants can design their marketing strategies to enable informational cascades to work for, and not against, them (Liu et al., 2020; Liu et al., 2016). Of course, no matter what marketing strategy is adopted, online retailers need to pay certain resources or costs. If the impact of information cascades on online consumer behavior in different countries is not the same, then online retailers that have entered e-commerce in different countries should use differentiated marketing strategies. Next, an important research question is whether the effect of information cascades on online shopping behaviors will be moderated by the consumers’ cultural orientation.