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.
TopIntroduction
Online auction becomes an important segment of electronic marketplaces as many buyers and sellers can buy and sell millions of products through this channel. eBay is the most popular auction house in the U.S. During Q2 in 2015, eBay has a record of 157 million active users, over 200% increase compared to the second quarter of 2005. It has new listings totaling a record of 800 million at any given time, 40% higher than those in the second quarter of 2005.
As buyers and sellers of online auctions are not able to meet face to face physically, trust built virtually between them is the key factor for transactions. Auction houses such as eBay have put many efforts in facilitating trust building between buyers and sellers. Among the tools, they used, the feedback system might be the most critical and successful mechanism to boost users’ trusts. The feedback system has two implications revealing sellers’ information. First, feedback scores are generally considered a good proxy for selling experience. The higher feedback scores, the more products that sellers have sold. Second, feedback scores and its positive percentage can represent seller reputation in online auctions. The higher feedback scores, the more buyers who do businesses with sellers. The higher positive feedback percentage, the higher likelihood that buyers are satisfied with their purchases. Therefore, gaining positive feedback ratings and avoiding negative feedback ratings, accumulating more feedback scores, and increasing the positive percentage help sellers survive and grow at electronic marketplaces.
While it is common knowledge that online auction feedback plays an important role in online trust building, to the best of our knowledge, the studies about eBay users’ post-transaction behavior on posting feedback ratings are limited. The ability of buyers and sellers to revoke or mutually withdraw negative feedback and ratings is discussed by Ye, Gao, & Viswanathan (2010). Jian, MacKie-Mason, & Resnick (2010) find that buyers and sellers on eBay carry out the “reciprocate only” strategy about 20-23% in feedback systems. Dellarocas, Fan, & Wood (2004) show that the probability sellers receive feedback ratings from buyers for successful auctions is on average about 70% at eBay. However, the details regarding buyers’ post-purchase reaction to online auction orders need more investigations.
This case study aims to address the not-fully-explored areas such as behavior on posting feedback ratings. We firstly compare the difference between new eBay users and experienced users in terms of post-purchase feedback postings to each other. Then, we look at the general issues in the positive, negative and neutral feedback ratings, respectively. By collecting and analyzing the data from eBay, we seek to answer the following specific questions:
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When do buyers send feedback to sellers if they would like to evaluate online auction orders and share their purchase experience?
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Do new sellers and experienced sellers have the same chance to get feedback from buyers? Particularly, the negative feedback from buyers?
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Who are more likely to post positive, neutral and negative feedback, respectively, new buyers or experienced buyers?
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Are there any differences between used and new products to receive feedback ratings?
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What are the most frequent issues related to positive, neutral and negative feedback, respectively?
This case study is to explore possible answers to these questions as an exploratory study (Stake 1995). The explorations of these questions could help us better understand buyers’ post-purchase behavior on feedback ratings, and provide sellers with constructive recommendations on effective selling strategies. For example, if new buyers are more likely to post negative feedback ratings than experienced buyers, sellers might need to take extra cautions dealing with new sellers. The most frequent words associated with negative feedback also offer insights into the common complaints from buyers; and help sellers reduce certain downside selling behaviors which are more likely to incur buyers’ complaints along with negative feedback.