Reputation dependent pricing strategy: analysis based on a Chinese C2C marketplace

TL;DR

This paper analyzes how reputation influences pricing strategies in a Chinese C2C marketplace, considering buyer information levels and seller reputation, supported by theoretical models and empirical data from Taobao.

Contribution

It develops models showing how buyer informativeness and competition affect seller pricing strategies based on reputation, with empirical validation from Taobao data.

Findings

High reputation sellers may charge lower prices with more informed buyers.

Negative price premium observed for TVs, laptops, cosmetics.

Price premium observed for beverages.

Abstract

Most online markets establish reputation systems to assist building trust between sellers and buyers. Sellers' reputations not only provide guidelines for buyers but may also inform sellers their optimal pricing strategy. In this research, we assumed two types of buyer: informed buyers and uninformed buyers. Informed buyers know more about the reputation about the seller but may incur a search cost. Then we developed a benchmark model and a competition model. We found that high reputation sellers and low reputation sellers adapt different pricing strategy depending on the informativeness of buyers and the competition among sellers. With a large proportion of informed buyers, high reputation sellers may charge lower price than low reputation sellers, which exists a negative price premium effect, in contrast to conclusions of some previous studies. Empirical findings were in consistence with our theoretical models. We collected data of five categories of products, televisions, laptops, cosmetics, shoes, and beverages, from Taobao, a leading C2C Chinese online market. Negative price premium effect was observed for TVs, laptops, and cosmetics; price premium effect was observed for beverages; no significant trend was observed for shoes. We infer product value and market complexity are the main factors of buyer informativeness.