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Understanding and Mitigating Product Uncertainty in Online Auction Marketplaces

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Angelika Dimoka Paul A. Pavlou

Anderson Graduate School of Management University of California, Riverside


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Understanding and Mitigating Product Uncertainty in Online Auction Marketplaces ANGELIKA DIMOKA


Anderson Graduate School of Management - University of California, Riverside

ABSTRACT The Internet interface poses a difficulty for buyers in evaluating products online, particularly physical experience and durable goods, such as used cars. This increases buyers’ product uncertainty, defined as the buyer’s perceived estimate of the variance in product quality based on subjective probabilities about the product’s characteristics and whether the product will perform as expected. However, the literature has largely ignored product uncertainty and mostly focused on mitigating buyer’s seller uncertainty. To address this void, this study aims to conceptualize the construct of product uncertainty and propose its antecedents and consequences in online auction marketplaces. First, drawing upon the theory of markets with asymmetric information, we propose product uncertainty to be distinct from, yet affected by, seller uncertainty. Second, based on auction pricing theory, we propose that product uncertainty and seller uncertainty negatively affect two key success outcomes of online marketplaces: price premium and transaction activity. Third, following information signaling theory, we propose a set of product information signals to mitigate product uncertainty: (1) online product descriptions (textual, visual, multimedia), (2) third-party product certifications (inspection, history report, warranty), (3) auction posted prices (reserve, starting, buy-it-now), and (4) intrinsic product characteristics (book value and usage). Finally, we propose that the effect of online product descriptions and intrinsic product characteristics on product uncertainty is moderated by seller uncertainty. The proposed model is supported by a unique dataset comprised of a combination of primary (survey) data drawn from 331 buyers who bid upon a used car on eBay Motors, matched with secondary transaction data from the corresponding online auctions. The results distinguish between product and seller uncertainty, show the stronger role of product uncertainty on price premiums and transaction activity compared to seller uncertainty, empirically identify the most influential product information signals, and support the mediating role of product uncertainty. This paper contributes to and has implications for better understanding the nature and role of product uncertainty, identifying mechanisms for mitigating product uncertainty, and demonstrating complementarities between product and seller information signals. The model’s generalizability and implications are discussed. Keywords: Product Uncertainty, Product Information Signals, Price Premiums, Online Auction Marketplaces, eBay Motors

Under 3rd round of Review in Information Systems Research November 2007

ACKNOWLEDGMENTS: We thank Izak Benbasat, Hasan Cavusoglu, Huseyin Cavusoglu, Ron Cenfetelli, Wynne Chin, Anindya Ghose, Steven Glover, Christian Wagner, Andy Whinston, and Robert Zeithammer for valuable feedback on earlier versions of this paper. The paper also benefited from feedback during presentations at the City University of Hong Kong, University of British Columbia, University of Houston, University of Oklahoma, UCLA, and University of Texas at Austin.

1. INTRODUCTION The global reach of online auction marketplaces allows buyers and sellers to overcome geographical and temporal constraints and purchase products anytime, from anywhere in the world. By leveraging the power of the Internet, online markets can improve consumer welfare wit