Learning from other buyers: The effect of purchase history records in online marketplaces
Introduction
Customers are often called on to make choices between different products, sellers and brands. With limited information on the value of these choices, customers often choose to follow other buyers. People observe the choices of other buyers in a variety of ways, including bestseller lists, the queue length in front of a teller, or the fraction of seats occupied in a restaurant. Despite these strategies, information about other buyers' choices can be noisy and hard to obtain in the offline world. With the emergence of online marketplaces, it has become much easier to observe other buyers' choices. global.eBay.com, the world's largest online marketplace, provides links to the purchase history records of listed items. Taobao.com, the leading online platform for C2C trading in China, lists the historical sales records for each item for the previous 30 days on each item's description page and allows buyers to sort the search results based on historical sales records. We examine the effect that a seller's historical sales records have on customers' purchasing decisions to answer the question: to what extent do customers learn from other buyers?
We argue that an item's purchase history signals its quality and the seller's credibility to the buyer. In online marketplaces where buyers and sellers are physically separated and the products cannot be examined before purchase, buyers face a considerate amount of uncertainty regarding both the quality of the product and the credibility of the seller. Online marketplaces such as eBay and Taobao provide feedback mechanisms that help to reduce this uncertainty. Many previous studies have analyzed the feedback scores or reputation ratings and detailed feedback text comments of online marketplaces. However, as many sellers sell more than one product on marketplaces like eBay and Taobao, these feedback scores/ratings tend to be overall assessments of the seller and may not be directly related to the item that a customer is looking for. Historical sales, on the other hand, are associated with individual items and might directly affect buyers' perceptions of product quality. We argue that customers are more likely to purchase from sellers whose items have higher historical sales records.
We investigate the effect that historical sales records have on purchase decisions by empirically analyzing the online data and by conducting a lab experiment. In the empirical investigation, we collect “buy it now” purchase data from eBay and Taobao. Auction purchases are excluded, because only the bidding history record for the particular auction is available on eBay. In contrast, the majority of Taobao transactions are completed as “buy it now” purchases [30]. We control for price and for a number of seller characteristics such as feedback scores/ratings, ratio of positive ratings, and in the case of Taobao, we also include Taobao-backed institutional guarantees. We find that across the variety of products we sampled, higher historical sales in a 30-day period are consistently associated with higher sales in the following seven days. In the lab experiment, we use an eye-tracking system to directly examine whether the participants pay attention to sellers' historical sales records.
Section snippets
Literature review and hypothesis development
Our study draws on previous research on online reputation, online word of mouth information cascades, and observational learning theories.
Many previous studies have investigated the role of online feedback mechanisms in building trust within online marketplaces [1], [17], [21]. Dellarocas [9] provided an excellent review of the research that has been done on eBay. These studies examined the effects of positive and negative feedback on price and probability of sale, with inconclusive results.
Data
The dataset for the empirical investigation consists of actual historical sales records and purchase records from Taobao.com and global.eBay.com. Taobao is the largest C2C platform in China and eBay is the largest C2C platform worldwide. They both provide sellers' historical sales information for each bidding item. Fig. 1 shows a seller's historical sales records for “Kingston DDRII 800 2 G Memory” on eBay. Fig. 2 shows a seller's historical sales records for “Kingston DDRII 800 2 G Memory” on
Experiment task and design
We conduct two lab experiments to further examine whether consumers use sellers' historical sales record information and how this information influences their purchasing decisions. The first experiment is a treatment experiment. In the experiments we track participants' eye movements as they browse C2C websites in a university laboratory. Participants view a webpage listing 20 shops in Taobao, all of which sell the same style of Dove chocolate. These 20 shops are real Taobao shops, chosen from
Implications
The results of this study have implications for the understanding of online marketplace reputation mechanisms. With the spread of online shopping, people are more likely to purchase products via online marketplaces. However, online shopping does not allow customers to inspect products, and this results in information asymmetry. Identifying product quality is a crucial issue for online customers. One practical solution is to establish a seller reputation mechanism. In this way, customers can
Conclusion
In our analysis of the transaction data from Taobao (the largest online marketplace in China) and eBay (the most popular online marketplace worldwide), we find that historical sales have a significant impact on a seller's current performance. More specifically, customers are more likely to choose sellers with more historical sales. This result indicates that buyers do take purchase history records into account when choosing a seller and making purchase decisions. Historical sales are
Acknowledgments
This research was partially funded by the Central Universities (HIT.BRET2.2010013), the National Science Foundation of China (71225003, 70971033), and the internal research grant of the School of Accounting and Finance at the Hong Kong Polytechnic University.
Qiang Ye is a Professor of Management Information Systems at Harbin Institute of Technology, Harbin, China. He received his Ph.D. in MIS from Harbin Institute of Technology in 2003. He had studied at the University of Texas at Austin during the 2006 academic year and at the Hong Kong Polytechnic University from 2007 to 2009. His research interests include e-commerce, e-tourism and business intelligence. Dr. Ye has published papers in Production and Operation Management, Decision Support Systems
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2021, Decision Support SystemsCitation Excerpt :As such, exogenous attention to social cues may distract endogenous attention from the product and anchor, thus negatively affecting purchase intention. However, several studies have observed the opposite effect: attention to peripheral social cues, such as purchase history records, could increase purchase intention because of the herding effect [9,21–23]. In other words, exogenous attention induced by social cues may have a positive spillover effect that influences consumer responses, providing another possible mechanism.
Qiang Ye is a Professor of Management Information Systems at Harbin Institute of Technology, Harbin, China. He received his Ph.D. in MIS from Harbin Institute of Technology in 2003. He had studied at the University of Texas at Austin during the 2006 academic year and at the Hong Kong Polytechnic University from 2007 to 2009. His research interests include e-commerce, e-tourism and business intelligence. Dr. Ye has published papers in Production and Operation Management, Decision Support Systems, International Journal of Hospitality Management and other journals. He is an Associate Editor of Journal of Electronic Commerce Research, and Area Editor of Electronic Commerce Research and Applications.
Zhuo (June) Cheng is an Associate Professor at the School of Accounting and Finance, Faculty of Business, Hong Kong Polytechnic University. She received her Ph.D. in MIS from the Ohio State University in 2005. Her research interests include information technology spillovers, technology diffusions, and reputation systems of online marketplaces. Dr. Cheng has published papers in Information Systems Research, Management Science, Information Technology and Management and other journals.
Bin Fang is a Ph.D. student of Management Information Systems at Harbin Institute of Technology, Harbin, China. He received his master's degree in MIS from Harbin Institute of Technology in 2011. His research interests include e-commerce and social network.
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Tel.: + 852 27664084.
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We use “purchase history records” and “historical sales records” interchangeably; the former term is used on eBay's list pages and the latter is used on Taobao's list pages.