Online Product Review, Product Knowledge, Attitude, and Online Purchase Behavior

Online Product Review, Product Knowledge, Attitude, and Online Purchase Behavior

Ching Seng Yap, Mor Yang Ong, Rizal Ahmad
Copyright: © 2017 |Pages: 20
DOI: 10.4018/IJEBR.2017070103
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This case study aims to investigate buyers' post-purchase behavior on feedback ratings. From the data collected from eBay, the statistical analysis shows that the average time length that buyers post their feedback after auctions completion is 15.5 days. New sellers and experienced sellers have different chances to receive feedback. New sellers are more likely to receive negative feedback over positive feedback. The distribution of the feedback types (negative, neutral and positive) does not match that of their associated monetary volumes. This case study also demonstrates that inexperienced eBay buyers are more likely to post negative feedback ratings than experienced ones. New and used products attract different ratings in the three feedback types. With word cloud and word frequency analysis, the authors identify common issues associated with each of the three types of feedback. The paper also discusses the managerial implications and recommendations based on these findings.
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Online product review is an important part of social networking activities. It refers to internet-mediated communities where experts and consumers exchange and share their experience and opinion about goods and services via online. Online product review is basically the communication between consumers and thus can be referred to as a type of electronic word-of-mouth or eWoM (Cheung et al., 2008; Lee et al., 2006, 2013). Online product review supplements other information provided by e-commerce firms such as product descriptions and recommendations from the automated systems (Mudambi & Schuff, 2010). Unlike the conventional word-of-mouth communities with their articulated opinions “disappear into thin air” (Dellarocas, Zhang, & Awad, 2007, p.24), online product reviews are public records posted on websites by experts and consumers that are persistent and easily accessible by others. For instance,, the e-commerce giant, which has allowed its customers to post ratings and comments about the products and services since 1995, has collected more than 35 million of consumer reviews across different product categories as of March 2013 (McAuley & Leskovec, 2013). With the proliferation of social media, consumer generated content is essential to many businesses in brand building (Chang et al., 2013), customer acquisition (Ahrens et al., 2013), quality control (Dellarocas, 2003), and market intelligence acquisition (Yap, Cheng, & Choe, 2014).

Online product review is argued as one of the key factors in influencing online purchase behavior. It can be in the form of text, audio, images or video to represent individuals’ positive, negative or neutral experience about products and services. Dellarocas et al. (2007) revealed that the use of online movie review makes it possible to generate early new movie post-release forecast more accurately which then facilitate allocation of exhibition capacity and screening room size for new movies. Zhu and Zhang (2010) found that online product review is more influential for less popular online games and its effectiveness is highly dependent on product and consumer characteristics. Vermuelen (2009) reported that online hotel reviews affect consumer decision making where both positive and negative reviews increase consumer awareness of hotels and positive reviews, in addition, improve attitudes towards hotels. However, Zhao et al. (2015) found a significant negative relationship between negative online reviews and online booking intentions. However, it is not the case for the influence of positive online reviews on booking intentions.

Various prior studies have investigated the role of online product review on sales of different products and services. For instance, book (Chen, Dhanasobhon, & Smith, 2007; Chevalier & Mayzlin, 2006), computer mice, calculator and red wine (Senecal & Nantel, 2004), digital camera (Gu, Park, & Konana, 2012), movie (Dellarocas et al., 2007; Duan, Gu, & Whinston, 2008; Liu, 2006; Moon, Bergey, & Iacabucci, 2010), video games (Zhu & Zhang, 2010), and hotel booking intentions (Kim, 2015; Vermeulen, 2009; Zhao, 2015). Most prior studies, with the exception of Gu et al. (2012), focused on low involvement products, and the ultimate dependent variable tested is either purchasing intention or sales. This study attempts to extend the studies by investigating actual purchase of high involvement product – toys, via online. This study develops and tests a conceptual framework to examine the relationships between online product review, consumers’ product knowledge, attitude towards online shopping and online purchase behavior in the online toy industry. With the opening of Legoland Malaysia Resort in 2012, toy products have gained increasing attention from the local consumers. In addition, the year 2014 witnessed the strongest growth for the toys and games industry in the past five years (Euromonitor, 2015) and Malaysia recorded a 9% current value growth in 2015. Nevertheless, research in this area receives relatively lower attention from academic researchers. Therefore, this research is important as it emphasizes actual online purchase of a high involvement product which has the potential to contribute to Malaysia’s economy.

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