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Journal cover: Internet Research

Internet Research

ISSN: 1066-2243

Online from: 1991

Subject Area: Information and Knowledge Management

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Remedies for information asymmetry in online transaction: An investigation into the impact of web page signals on auction outcome


Document Information:
Title:Remedies for information asymmetry in online transaction: An investigation into the impact of web page signals on auction outcome
Author(s):Chung-Chi Shen, (Graduate Institute of Marketing and Logistics, National Chiayi University, Chiayi, Taiwan), Jyh-Shen Chiou, (College of Commerce, National Chengchi University, Taipei, Taiwan), Biing-Shen Kuo, (College of Commerce, National Chengchi University, Taipei, Taiwan)
Citation:Chung-Chi Shen, Jyh-Shen Chiou, Biing-Shen Kuo, (2011) "Remedies for information asymmetry in online transaction: An investigation into the impact of web page signals on auction outcome", Internet Research, Vol. 21 Iss: 2, pp.154 - 170
Keywords:Auctions, Electronic commerce, Information exchange, United States of America
Article type:Research paper
DOI:10.1108/10662241111123748 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – This study seeks to investigate the signals on which consumers may rely to reduce the problems of information asymmetry on an online auction site. The research aims to develop and test based on information signaling theory. It classifies signals from auction web pages into three types: seller reputation, product condition, and argument quality. To understand how the signals affect consumers' online buying decisions, the study intends to test the impacts of these signals on the auction outcome variables: number of bids, auction success, and willingness to pay.

Design/methodology/approach – The paper employs an empirical test with real observation data comprised of 5,013 samples coded from the eBay auction site in the USA. Ordinary least squares (OLS) regression is used to predict the effect of web page signals on the number of bids, logistic regression to determine which web page signals contribute to auction success, and Tobit maximum likelihood estimation to estimate the impact of web page signals on willingness to pay.

Findings – Results show that, in addition to the seller's reputation, signals like product condition and the quality of the sellers' arguments on the web page are significantly related to the three auction outcomes. Buyers tend to rely on these signals to resolve information asymmetry in online auction transactions.

Originality/value – Past studies have found that the seller's feedback score is central to a positive online auction outcome. This paper is the first to classify web page signals comprehensively and to investigate their impacts on online auction outcomes using real transaction data. The findings provide substantial evidence and implications for both academic research and practitioners in online auctions. A dynamic strategy for success in online auctions is offered in the conclusion section.



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