Follow the Leader? Strategic Pricing in E-Commerce

Conventional wisdom and current research (e.g., Bakos 1997) suggest that the Internet will lower electronic commerce (EC) product prices by causing intense competition among EC firms. Surprisingly, the predicted intense competition has not materialized. Sager and Green (1998) ask, “So where are all the bargains?” and note that EC firms match, (not beat), competitors’ prices. Firms retrieve competitors’ prices using the same EC shopbot technology that allows buyers to search for the best prices (Varian 2000). Thus, information asymmetry among EC firms is reduced, opening a new spectrum of competitive possibilities. We examine the dynamics of EC product pricing using research from information systems (IS) (Bakos 1997; Brynjolfsson and Smith 1999), marketing (Alba et al. 1997; Bailey 1998; Lal and Sarvary 1999) and economics (Varian 2000) as a base. We conduct a multi-industry investigation of pricing behavior using a customized data-collecting Internet agent called Time Series Agent Retriever (TSAR). Information asymmetry and tacit collusion theories show how EC technology increases firms’ ability to tacitly collude. Our results, analyzed using an econometric technique called vector autoregression (V AR) (Sims 1980, 1986), show that EC technology reduces information asymmetry among EC firms and allows rapid competitor response, allowing firms to avoid competition