5. AN EXPLORATORY ANALYSIS OF INTERNET COMMERCE
5.4. A NALYSIS
5.4.4. Price Discrimination
The Internet consumer may be signaling that they have a higher willingness-to-pay and, in response, the Internet retailers are charging higher prices. Because the current users of the Internet, as described by Hoffman, Novak, and Chatterjee. (1996), are mostly educated, higher income users they may be less price sensitive than the consumers in the general population who shop at physical retailers. Internet retailers, knowing that their consumers are more affluent, are able to charge a higher price because their consumers have self-selected from the average user (Varian 1997). Furthermore, consumers who shop on the Internet may place a premium on the convenience of having goods delivered directly to them, instead of having to visit a physical store.
If demographics, convenience and price discrimination are driving the pricing differentials between Internet and physical retail prices, then the price differentials for the book, CD and software markets will not necessarily be the same. In particular, because virtually all consumers in the software market have computers, and are likely to therefore have demographics similar to those of Internet users in general, it may be more difficult to make inferences
about their willingness-to-pay based on their choice of channel.63 In other words, software consumers who shop on the Internet do not particularly distinguish themselves from the software consumers who shop at physical retailers.
This is less likely to be true for books and CDs. Consistent with this hypothesis, the data in Table 5.1 indicates that the software market has the lowest differential between average Internet retailer and physical store retailer.
Under this hypothesis, the higher Internet prices in the book and CD markets may not be sustainable as more people gain Internet access and the demographics of Internet consumers thus match those of the general population more closely. As technologies such as WebTV and general Internet use grows, the signaling to retailers decreases and the fact that a particular consumer shops on the Internet does not necessarily mean they have a higher willingness-to- pay. The software market may have consumers who are the earliest adopters of Internet commerce and thus reflect the leading edge of pricing.
A fourth hypothesis is a twist on the signaling explanation described above. There is a possibility that the prices posted on the Internet by the retailers with physical stores are not constrained to be the same as the prices they charge to consumers who walk into their stores. As noted above, Shepard’s (1991) model of service differentiated competition predicts that firms who sell through multiple channels will, if possible, set lower prices in their low service channel than firms who sell through only one channel. This prediction could explain the finding that prices charged by retailers with physical stores seem to be lower in some markets than prices charged by Internet retailers.
Specifically, it may be that the prices that the “physical” stores post on the Internet are lower than the prices they charge to consumers who walk into their stores. However, to apply Shepard’s model to the data requires two critical assumptions.
The first assumption is that Internet retailers have market power. In this setting market power could arise through a variety of sources. Brand recognition may give one retailer an advantage over another just as Barnes & Noble’s brand name is well know as a physical bookseller. The reputation of an Internet retailer can help increase market power . For example, numerous positive stories about Amazon.com’s in the popular press may give them market power. Prior experience may also lead to market power. For example, if a consumer bought from Books-A-Million in the past they may not want to risk dealing with someone else. Market power arising from these sources is more likely in the early stages of Internet commerce where few Internet stores have established brand names, consumers are less aware of the different retailers on the Internet, and consumers may be skeptical of the reliability and reputability of Internet retailers. Thus, the ability of firms who sell through multiple channels to price discriminate may decline over time. Of course, the assumption that Internet retailers have market power is directly contrary to the hypothesis of Bertrand competition on the Internet.
63 Zettelmeyer (1995) describes a variant of this explanation in greater detail, although his model assumes that it is the Internet shoppers who will initially face lower prices.
The second assumption is that, ceteris paribus, consumers prefer the “high service” shopping experience of physical stores to the “low service” experience of shopping on the Internet and will therefore pay a premium for it. This is similar to the findings of Shapiro (1983). In this work, Shapiro describes price differences as a result of investment in increasing the quality of the goods to promote a positive reputation with consumers. These preferences could arise because consumers prefer to have access to salespeople who can make recommendations, or because it is easier to compare different products in a physical setting. As Preston (1962; 1963) shows, there can be price competition among retailers but the price does not converge to one price because the retailers have different products targeted as loss leaders.
However, regardless of how the preference for high service arises, it must dominate the increased convenience of shopping for products over the Internet. One could imagine that service would dominate convenience when consumers come to a store to browse for goods rather than when consumers already know what good they want to buy. Thus, markets where consumers frequently browse for goods may experience a larger physical to Internet price differential than markets where consumers do not browse as frequently.
In light of this service differential, it is interesting that some retailers are actively attempting to counter the potential service advantages of physical stores. For example, Amazon.com allows consumers to post reviews of books they have read. Likewise, the Internet retailer Music Boulevard (among others) allows consumers to sample songs from CDs before purchasing. Given that physical retailers profit by maintaining a distinction between “high” and “low”
service channels, physical retailers may use the Internet as a service channel to distinguish it from physical channels.
Furthermore, retailers that use the Internet exclusively as a service channel may more aggressively attempt to reduce the service distinction between Internet and physical channels to reduce their competitor’s higher profits from such a price discrimination strategy. This prediction will be explored more fully through future research and data collection.
It is also possible that prices are different on the Internet because retailers who sell products in both Internet and physical markets have different pricing strategies than retailers who sell products in only one market or the other.
Shepard (1991) considers such an environment in her study of the consumer market for self- and full-service gasoline. Her model shows that if consumers differ in their willingness-to-pay for service, retailers who offer both levels of service will engage in discriminatory pricing—setting lower prices in low service markets and higher prices in high service markets than retailers who only offer one service level.
Specifically, Shepard considers a model where consumers have unitary demand and utility functions that are separable in income and consumption. The resulting consumer preferences are given by
U =
V(g)(t - pg) if the consumer purchases one unit of service level g (high or low) V(0)t if the consumer does not purchase
where V(g) is consumer utility from purchasing one unit of service level g, V(0) is consumer utility from not purchasing, t is the consumer’s normalized income level assumed to vary uniformly on the interval [0,1], and pg is the normalized price of one unit of service level g. If a retailer sells through only one channel, consumers will purchase if their utility to purchasing at pg exceeds their utility from not purchasing. The resulting demand is given by
D(pg) = 1 – V(g)pg V(g) - V(0)
If a retailer sells through both high and low service channels, consumers will purchase service level g if their resulting utility exceeds both what they could get by not purchasing and what they could get by purchasing the other service level. Given that consumers prefer high to low service, the resulting demand for the low service good is given by
Dl(pl, ph) = V(h)ph
V(h) - V(l) + V(l)[V(h) – V(0)]pl [V(h) – V(l)][V(l) – V(0)]
where the subscripts h and l index the high and low service levels respectively.
Retailers who sell through only one channel will set prices to maximize profits from the one channel. For low service retailers the resulting price is given by
pl SC =
SC argmax
( pl – cl) D(pl)
where the superscript SC indicates a single channel retailer and cl is the retailer’s marginal cost for low service.
Likewise, retailers who sell through both channels will set prices to maximize the sum of profit through both channels. The resulting price for the low service good is given by
pl MC =
MC argmax
[( ph – ch – cl ) Dh(ph, pl ) + (pl –cl ) Dl(pl, ph )]
where the superscript MC indicates a multiple channel retailer and ch is the retailer’s marginal cost for high service.
Shepard goes on to show that p l MC ≤ p
l SC and p
h MC ≥ p
h SC64
. Shepard confirms these predictions through empirical data on gas station prices which show that retailers who offer both self- and full-service have a $0.04 higher price differential than the differential among retailers who sell only one level of service. In the Internet marketplace, this model corresponds to a situation where retailers have market power (which could be based on brand name or reputation). In this environment, a consumer purchasing books from Barnes & Noble would choose to purchase over the Internet or through a physical store based on their reservation price for service or convenience. Knowing this, Barnes & Noble would price its goods to separate consumers based on these characteristics. The resulting equilibrium would have retailers who sell using both Internet and physical channels setting lower prices on the Internet than stores who sell only through the Internet. The implications of this model for the data are discussed in more detail in the Analysis section.