NETWORK EFFECTS AND COMPETITION: :: essays research papers

In many industries, the network of consumers using compatible products or services influences the benefits of consumption. Positive network effects arise when the consumer utility of using a product or service increases with the number of users of that product or service. The telephone system is a widely used example since it seems clear that the value of being part of the network rises as the network sizes increases. Consumption benefits can also arise in markets where a large customer network leads to increases in complementary products and services, which in turn, leads to increased consumer utility (e.g., see Farrell and Saloner 1985; Katz and Shapiro 1985;1986). Prominent examples of industries thought to exhibit network effects include automated bank teller machines, computer hardware and software, videocassette recorders, video games, and Internet web browsers. Not surprisingly, network externalities and the implications of having a large installed customer base are receiving increased attention by strategy researchers (e.g., Garud and Kumaraswamy 1993; Hill 1995; Wade 1995). As noted by Majumdar and Venkataraman (1998), the literature related to network effects broadly tackles three categories of research questions: (1) technology adoption decisions (e.g., what factors are related to whether and when a new technology is adopted), (2) technology compatibility decisions (e.g., what factors influence a firm’s decision to seek compatibility), and (3) decisions among competing incompatible technologies (e.g., what factors are related to consumers’ choices among rival incompatible products within a single product category). While theoretical research has addressed all three of these categories, empirical research has been limited to the first and second categories of questions (e.g., see the reviews in David and Greenstein 1990; Liebowitz and Margolis 1994; Economides 2001). Empirical efforts supporting the existence of network effects for a single product technology show that a larger network size is related to higher minicomputer sales (Hartman and Teece 1990), higher likelihood of adopting a new telecommunications technology (Majumdar and Venkataraman 1998), and quicker adoption of a new banking technology (Saloner and Sheppard 1995). In addition, Gandal (1994; 1995) and Brynjolfsson and Kemerer (1996) use a hedonic price model to show that consumers are willing to pay higher prices for software products that are compatible with the dominant product standard, i.e., the product with the larger customer network. However, with the exception of a few industry case studies (e.g., Gabel 1991; Grindley 1995; Liebowitz and Margolis 1999), we are unaware of any published studies that empirically investigate the nature of network effects in an industry with multiple competing product technologies that are incompatible.