A classification of online bidders in a private value auction: evidence from eBay

Hou, Jianwei; Rego, César

doi:10.1504/ijemr.2007.014847

Cited by 17 publications

(10 citation statements)

References 32 publications

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“…While there does appear to be considerable empirical research about on-line auction management, little of this research speaks directly to the charity organization's issues. For instance, Hou and Rego ( 2003 ) identified four types of bidders, namely, goal-driven bidders, experiential bidders, playful bidders, and opportunistic bidders. The opportunistic bidders on average pay the lowest price.…”

Section: Background Of Auctions In Virtual Spacementioning

confidence: 99%

Charity Auctions on the Internet: An Exploratory Study

Chua¹,

Berger²

2021

Preprint

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The purpose of this study is to explore the value of conducting auctions on-line as a method of raising funds for charity organizations. We review the relevant literature on auctions, in both on-line and live formats and find that there remain numerous unanswered questions for charities considering this funding mechanism. In this exploratory study we collect and compare bid and selling information from eBay’s standard and charity sites and conclude, surprisingly, that the auction clearing prices for comparable items are higher on the non-charity site. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series,TRSM, Ted Rogers School of Management Citation:

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Section: Background Of Auctions In Virtual Spacementioning

confidence: 99%

Charity Auctions on the Internet: An Exploratory Study

Chua¹,

Berger²

2021

Preprint

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“…We consider a private-value auction where each bidder knows his valuation for the item, which is independent of others' valuations. The private-value setting has been supported by extensive literature that has empirically studied online auction platforms like eBay (Hou & Rego, 2007;Ockenfels & Roth, 2006;Roth & Ockenfels, 2002;Zeithammer, 2006). The seller has no intrinsic value for the good, and therefore, her reservation price is zero.…”

Section: Modelmentioning

confidence: 99%

Targeted Couponing in Online Auctions

Choudhary

Shivendu

2017

Information Systems Research

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In order to study the role of targeted couponing in auctions, we develop a stylized model in which bidders have heterogeneous valuations and participation costs wherein their entry probabilities are endogenous.Couponing impacts the seller's profit in two ways: (i) impact on bidders' entry probability including negative externalities for the bidder who does not receive a coupon and (ii) value extraction. We find that targeting a coupon to the low-valuation bidder can be optimal for the firm even if it leads to a reduction in the joint entry probability of the two bidders because of the benefit from value extraction. A novel result is that in the context of auctions it can be optimal for the seller to issue targeted coupons to the high-valuation bidder. We also find that an increase in the bidders' valuation or reduction in the participation cost can lead to lower profit for the seller. This result is driven by the non-monotonicity of the joint entry probability of the two bidders and the seller profits being non-monotone functions of bidders' valuations and participation costs.

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“…The analysis revealed that there were certain bidding behaviors that appeared frequently in online auctions. Hou and Rego used hierarchical clustering to generate four distinct groups of bidding behaviors for standard eBay auctions, namely goal-driven bidders, experiential bidders, playful bidders, and opportunistic bidders [14]. They concluded that online bidders were a heterogeneous group rather than a homogenous one.…”

Section: Related Workmentioning

confidence: 99%

“…Bidder Feedback Rating (BFR) is useful in describing a bidder's experience level and established trustworthiness [8,14]. However, we should also notice the potential for fabricating feedback rating through collusion between misbehaving users and fraudulent bidding rings [2,4].…”

Section: User Attributesmentioning

confidence: 99%

A Real-Time Self-Adaptive Classifier for Identifying Suspicious Bidders in Online Auctions

Ford

Valova

2012

The Computer Journal

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With the significant increase of available item listings in popular online auction houses nowadays, it becomes nearly impossible to manually investigate the large amount of auctions and bidders for shill bidding activities, which are a major type of auction fraud in online auctions. Automated mechanisms such as data mining techniques were proven to be necessary to process this type of increasing workload. In this paper, we first present a framework of Real-Time Self-Adaptive Classifier (RT-SAC) for identifying suspicious bidders in online auctions using an incremental neural network approach. Then we introduce a clustering module that characterizes bidder behaviors in measurable attributes and uses a hierarchical clustering mechanism to create training datasets. The neural network in RT-SAC is initialized with the training datasets, which consist of labeled historical auction data.Once initialized, the network can be trained incrementally to gradually adapt to new bidding data in real-time, and thus, it supports efficient detection of suspicious bidders in online auctions. Finally, we utilize a case study to demonstrate how parameters in RT-SAC can be tuned for optimal operations and how our approach can be used to effectively identify suspicious online bidders in real-time.

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A classification of online bidders in a private value auction: evidence from eBay

Cited by 17 publications

References 32 publications

Charity Auctions on the Internet: An Exploratory Study

Charity Auctions on the Internet: An Exploratory Study

Targeted Couponing in Online Auctions

A Real-Time Self-Adaptive Classifier for Identifying Suspicious Bidders in Online Auctions

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