Abstract

The Internet interface poses a difficulty for buyers in evaluating products online, particularly experience goods, such as used cars. This increases product uncertainty, the buyer’s estimate of the variance in product quality. However, the literature has ignored product uncertainty and focused on seller uncertainty. To address this void, this study examines the nature, effects, and antecedents of product uncertainty in online auctions for used cars. Extending the literature on markets with asymmetric information, we first conceptualize the construct of product uncertainty and show that is distinct from, yet related to, seller uncertainty. Second, we propose product uncertainty to negatively affect two key success outcomes of online marketplaces - price premiums and transaction activity - beyond seller uncertainty. Third, we propose a set of product information signals to mitigate product uncertainty: (1) the diagnosticity of online product descriptions (textual, visual, multimedia), (2) the level of auction posted prices (reserve, starting, buy-it-now), (3) the existence of third-party product certifications (inspection, history report, warranty), plus intrinsic product characteristics (book value, usage). 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 that product uncertainty has a stronger effect on price premiums and transaction activity than seller uncertainty, identify the most influential product information signals, and validate the mediating role of product uncertainty. The study contributes to and has implications for understanding the nature and role of product uncertainty, and identifying how product uncertainty can be mitigated in online environments with the aid of IT.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call