Assessing success factors of selling practices in electronic marketplaces

Electronic markets have early emerged as an important topic inside e-commerce research. An e-market is a digital ecosystem intended to provide their users with online services that will facilitate information exchange and transactions. This work presents a characterization and analysis of fixed-price online negotiations. Using actual data from a Brazilian marketplace, we analyze selling practices, considering seller profiles and selling strategies. There are important factors that can be considered when analyzing selling practices, such as the seller's reputation and experience, offer's price, duration, among others. We evaluate which factors impact on the success of selling practices in e-markets, which can be used to support seller's decision and recommend selling practices. Moreover, we investigate some important hypotheses about selling practices in online marketplaces, which allow us to state interesting conclusions, such as: a seller profile can achieve success or not in a trade, depending on the adopted strategy; the offer's price and how it is being advertised are two important success factors.

[1]  Steven T. Anderson,et al.  Buy it Now: A Hybrid Internet Market Institution , 2004 .

[2]  Thuong T. Le,et al.  Pathways to Leadership for Business-to-Business Electronic Marketplaces , 2002, Electron. Mark..

[3]  John Wooders,et al.  Auctions with a buy price , 2004 .

[4]  Jan-Mou Li,et al.  Key factors in forming an e-marketplace: An empirical analysis , 2006, Electron. Commer. Res. Appl..

[5]  David Lucking-Reiley,et al.  Using field experiments to test equivalence between auction formats: Magic on the internet , 1999 .

[6]  Steven T. Anderson,et al.  Seller Strategies on eBay , 2004 .

[7]  Tomas Klos,et al.  Trusted intermediating agents in electronic trade networks , 2005, AAMAS '05.

[8]  Durham Yvonne,et al.  eBay's Buy-It-Now Function: Who, When, and How , 2004 .

[9]  Hans-Hermann Bock Data mining tasks and methods: Classification: the goal of classification , 2002 .

[10]  Dorin Militaru,et al.  Consumer behavior in electronic commerce environments and fashion effect , 2007, ICEC.

[11]  Nikos Manouselis,et al.  Studying Research on E-Markets during 1995-2005 , 2008, WSKS.

[12]  Paul A. Pavlou,et al.  Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior , 2002, MIS Q..

[13]  K. Reynolds,et al.  Determinants of internet auction success and closing price: An exploratory study , 2003 .

[14]  R. Becherer,et al.  Characteristics and internet marketing strategies of online auction sellers , 2004 .

[15]  Yves Lechevallier,et al.  Pre-Processing and Clustering Complex Data in E-Commerce Domain , 2005 .

[16]  Nicholas R. Jennings,et al.  Sellers Competing for Buyers in Online Markets: Reserve Prices, Shill Bids, and Auction Fees , 2007, IJCAI.

[17]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[18]  Jie Zhang,et al.  An incentive mechanism for eliciting fair ratings of sellers in e-marketplaces , 2007, AAMAS '07.

[19]  Joan Feigenbaum,et al.  Computational challenges in e-commerce , 2009, CACM.

[20]  Andrew W. Moore,et al.  X-means: Extending K-means with Efficient Estimation of the Number of Clusters , 2000, ICML.

[21]  Nicholas R. Jennings,et al.  The effects of proxy bidding and minimum bid increments within eBay auctions , 2007, TWEB.

[22]  Ramanathan V. Guha,et al.  Propagation of trust and distrust , 2004, WWW '04.

[23]  Paul Resnick,et al.  Trust among strangers in internet transactions: Empirical analysis of eBay' s reputation system , 2002, The Economics of the Internet and E-commerce.

[24]  Ali Hortaçsu,et al.  Winner's Curse, Reserve Prices and Endogenous Entry: Empirical Insights from Ebay Auctions , 2003 .

[25]  Yishay Mansour,et al.  An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering , 1997, UAI.

[26]  Virgílio A. F. Almeida,et al.  Analyzing seller practices in a Brazilian marketplace , 2009, WWW '09.