Sellers in Online Auction Markets: Introducing a Feedback-Based Classification

Abstract

Increasing significance of the online consumer-to-consumer (C-2-C) auction market has amplified the need for buyers and sellers to engage in transactions with anonymous counterparts. The sequence of paying first and then taking delivery, introduces a great amount of risk for potential buyers. In order to mitigate this risk, online auction markets (OAMs) are employing an assortment of governance mechanisms, of which reputation scoring and reporting systems are the most popular. Researchers have found substantial evidence from theoretical models as well as empirical studies that higher the reputation rating of a seller, higher the bid prices he/she receives. However, a review of the current literature suggests a conspicuous absence of any standard classification of sellers in OAMs. Lack of such a classification hinders systematic research and theory development. Therefore, a comprehensive classification of sellers, based on feedbacks, is proposed to advance our understanding of online C-2-C auction market and to provide a basis for further research. In addition, the proposed classification is hierarchical rather than monothetic in nature and hence, gives greater systemic power to the classification. Toward demonstrating the classification’s systemic power, we present a propositional inventory developed from the classification. We also discuss how the proposed classification accommodates current research and furthers theory building in this research area.