مقاله انگلیسی رایگان در مورد درک محتوای متنی بررسی آنلاین مشتریان در سایت B2C ( الزویر )

مقاله سال 2017

Online shopping flourished and became increasingly popular in recent years (Bagdoniene and Zemblyte, 2015; Clemes, 2014). Most B2C websites support and encourage post-purchase consumers to write reviews on their sites. Online customer reviews (OCRs) reflect the shopping and product usage experiences of consumers.

OCRs provide sellers with genuine, convenient, and low-cost firsthand market information and potential customers with vital decision-making information. Customers read the textual content of OCRs rather than rely only on summarized statistics (Chevalier and Mayzlin, 2006). OCRs are important information sources for sellers to attract new customers and manage regular clients (Chevalier and Mayzlin, 2006; Hu et al., 2008; Sparks and Browning, 2010). The textual content of OCRs is key to understand the effect of these reviews (Godes et al. 2005; Moore, 2012; Shin and Biocca, 2017). Hence, the textual content of OCRs should be urgently examined.

However, previous studies mainly focus on the statistical characteristics of the content of OCRs, such as review valence, quantity, extremity, depth, diversity, density, and length (Cao et al., 2011; Chevalier and Mayzlin, 2006; Hu et al., 2008; Korfiatis et al., 2012; Mudambi and Schuff, 2010; Qazi et al., 2016; Willemsen et al., 2011). Previous works overlooked the narrative content of OCRs (Moore, 2012). According to Hong and Park (2012), narrative OCRs have important effect on consumer attitude toward product as well as statistical OCRs. In practice, consumers rely on both statistical and narrative OCRs when evaluating a product. Sellers rely on narrative OCRs to form comprehensive understanding of consumer experience. Thus, the textual content of OCRs should be explored. In order to understanding the textual content of OCRs more systematically, one aim of the present study is to propose the dimensions of the textual content of OCRs, which has contribution to construct analysis framework of the textual content of OCRs.