Understanding and Mitigating Product Uncertainty in Online Auction Marketplaces

53 Pages Posted: 21 May 2008

See all articles by Paul A. Pavlou

Paul A. Pavlou

Temple University - Department of Management Information Systems; Temple University - Department of Strategic Management

Angelika Dimoka

Temple University - Department of Marketing and Supply Chain Management; Center for Neural Decision Making, Temple University

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

Suggested Citation

Pavlou, Paul A. and Dimoka, Angelika, Understanding and Mitigating Product Uncertainty in Online Auction Marketplaces. 2008 Industry Studies Conference Paper. Available at SSRN: https://ssrn.com/abstract=1135006 or http://dx.doi.org/10.2139/ssrn.1135006

Paul A. Pavlou (Contact Author)

Temple University - Department of Management Information Systems ( email )

1810 N. 13th Street
Floor 2
Philadelphia, PA 19128
United States

Temple University - Department of Strategic Management ( email )

Fox School of Business and Management
Philadelphia, PA 19122
United States

Angelika Dimoka

Temple University - Department of Marketing and Supply Chain Management ( email )

Philadelphia, PA 19122
United States

Center for Neural Decision Making, Temple University ( email )

Philadelphia, PA 19122
United States

HOME PAGE: http://www.fox.temple.edu/minisites/neural/index.html

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