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Top1. Introduction
The most popular type of e-commerce is business-to-consumers (B2C) throughout the world, which includes e-shopping (Anu Gupta Aggarwal & Aakash, 2018). B2C refers purchasing not only from brick-and-mortar stores, such as Big Bazaar, marks & spencer, etc., but also from internet based e-tailers such as Amazon.com (Aggarwal & Aakash, 2017; Anu G Aggarwal & Aakash, 2018). In 2018, an estimated 1.79 billion people across the globe bought product online (statista, 2018a). During 2018, the global e-retail sales is around 2842 billion U.S. dollars and it will be around 4878 billions U.S. dollars till 2021 (statista, 2018b). The rapid growth of e-commerce has led to an enormous amount of electronic-word-of-mouth (EWOM) on product information and performance by actual users of that product. Around 90% online consumers read EWOM (review) text before purchasing products online (BrightLocal, 2016). More than 80% people trust EWOM as much as a personal recommendation (BrightLocal, 2016).
Research studies on the role of electronic word of mouth in online markets have been undertaken at two levels-first at the consumer level where the researchers have analyzed the impact of EWOM on the individuals in terms of their buying behavior and loyalties online. According to Sahoo, Dellarocas, and Srinivasan (2018), EWOM aid customers purchasing intention. Aakash and Aggarwal (2019) proposed that EWOM is an antecedent of e-commerce customer satisfaction as well as repurchase intention. The quality and credibility of online reviews influence customers' repurchase intention positively (Matute, Polo-Redondo, & Utrillas, 2016). EWOM has also a direct relationship with loyalty intentions (C. Park & Lee, 2009). The second level is market specific. In these types of studies the role of EWOM content on product sales, hotel bookings, movie ticket sales etc. have been reported. These markets specific studies focus on EWOM information characteristics along with product price on the sales of the product/service (Wenjing Duan, Bin Gu, & Andrew B Whinston, 2008a; Hong, Xu, Xu, Wang, & Fan, 2017; Moon, Park, & Seog Kim, 2014; Wu, Du, & Dang, 2018; L. Zhang, Ma, & Cartwright, 2013).
In these studies, the review content information is measured in terms of review length, review ratings, review volume, product ratings etc. but review readability remains as underexplored area in these researches. According to Chua and Banerjee (2016), the review readability represents the comprehensibility of the information contained of the text of the reviews. And it measures the degree to which the text is easy to understand. The potential customers may easily understand the feedback of previous buyers if review text has higher readability or they may ignore those EWOM which are too simple to read. Fang, Ye, Kucukusta, and Law (2016) identified that when a EWOM text was easier to read it would get more helpful ratings while Archak, Ghose, and Ipeirotis (2011) found that readable EWOM is sometimes overlooked for being too simplistic. Figure 1 shows the consumer experience expressed through EWOM about iPhone-8 bought from Amazon.com. Not only the length of this EWOM is large, but also it is easy to read, and only 22 people found this review helpful.
Figure 1. An example of EWOM related to cellphone on Amazon.com
In Figure 2, another consumer review related to cellphone at Amazon.com has less review length and little bit hard to read as compared to the review shows in Figure 1, but has 109 helpful votes. Hence, the relationship between product sales and EWOM readability remains a mystery. Therefore, there is a need to understand the impact of EWOM readability on the product sales in e-shopping.
Figure 2. An example of EWOM related to cellphone on Amazon.com