Internet Prices and Price Dispersion

Background

During early days of e-commerce, retailers selling search goods, such as books and CDs, first emerged. The rise of consumer confidence, coupled with the development of information technology, has led (more expensive) experience goods to the new economy. This trend is indicated by the delayed entrance of luxury goods onto the online marketplace. One direct benefit of participating in e-commerce is cost savings for retailers, although it is less clear to which extent consumers benefit from these savings. To examine this issue, one strand of the literature compares prices of matched products sold in both online and brick-and-mortar stores. Most studies have documented lower online prices in various industries (see in Table 1), indicating the relative efficiency of e-commerce.

Online shoppers enjoy enhanced search capability through effective tools. Search sites, such as Google and Yhaoo!, have become indispensable for comparison shopping. A recent comScore Media Matrix monthly qSearch™ analysis reports a total of 18.8 billion unique desktop search queries submitted in January 2015.¹ With the rising popularity of mobile devices, from smartphones to tablets, one would only expect a greater utilization of search engines.² However, the prevalence of search engines needs not eliminate all barriers to perfect competition among e-retailers, as recent research still reports persistent price dispersion (e.g., Jin & Kato, 2006 on ungraded baseball cards; Baye & Morgan, 2009 on consumer electronics; Chellappa et al., 2011 on airfares; Ghose & Yao, 2011 on service supply products; Dinerstein et al., 2014 on video games). The empirical literature has developed several measures of price dispersion:³ In a given product market,

• •

  Price Range: The difference between the highest and the lowest price.

• •

  Percent Price Range: The ratio of price range to the lowest price.

• •

  Coefficient of Variation: The ratio of the standard deviation to the average price.

• •

  Gini Coefficient: where p_i is the price of observation i, with i=1,2,…, N, λ is the mean price. (Gaggero & Piga, 2009).

• •

  Price Gap: The price difference between the two lowest-priced firms (Baye et al., 2004).