Introduction
Just as the Internet has had an impact on the market for information goods and services, it has also had an impact on the information necessary for markets to function. Perfectly competitive markets, upon which models of economics are based, require four key characteristics:
- Many sellers.
- Nearly identical products.
- Easy market entry (and exit).
- Buyers and sellers have perfect information.
The last point is possibly the most difficult. Good information is hard to come by, let alone perfect information, for both buyers and sellers. Buyers are perhaps at a disadvantage, but the rise of the online marketplace and specifically price aggregating web sites has created an interesting change.
Background
As soon as the World Wide Web began gaining popularity, people began using it to sell things. How do price aggregation sites like pricegrabber.com, bizrate.com, mysimon, shopper.cnet.com, etc., impact buyers and sellers?
Economic Principles
Network effects are important on both the buyer’s and seller’s side of this new online market. The two form a sort of positive feedback loop: as more sellers allow their goods to be listed at a site like those discussed above, more customers will be drawn to that particular site. As more customers are drawn, more sellers will want to access this market. A price aggregation and recommendation site with information about only five retailers is almost useless. If that site doubles or quadruples their listed retailers, it suddenly begins to produce value for buyers, even if nothing else on the site has changed and no other services have been introduced. If that site brings their list to 50 or 100, there’s a good chance that it now reflects the entire market for some items and offers buyers the value of price omniscience.
The network effects of seller information collection to buyers are important, but the effect of buyer-to-buyer information collection are perhaps even more striking. Imagine a traditional web site that reviews digital cameras. Most sites like this will only have one review of each camera, with perhaps a few links to reviews on other sites. Also, few websites have the time or budget to review every single camera on the market. Now, the user can take or leave the review, can ignore or heed the reviewer’s recommendation, but one review, however in-depth, is a poor reflection of the universe of experience with the product. A camera could have a 20 % failure rate, for example, and four out of five reviewers might not notice. Now imagine an aggregation site with one user comment—it is similarly hampered. An aggregation site with five, or 10, or 20 reviews is much more likely to represent the true overall experience—even grad students know this; for example, at least five cases are needed in each cell of a bivariate analysis for a Chi-Square to be even worth doing, and chances for statistical significance are slight without a few more than that.9
Information overload.
Much has been made of the notion that access to so much information has put Americans on the precarious cliff of “information overload,” beyond which no one will be able to wade through all the stuff to get at what they need or tear themselves away from facts and figures to actually get stuff done.
Let’s look at it from a more economic point of view. Every action an actor in a market can take has an opportunity cost—whenever time is spent, the possibility that the time could have been spent otherwise is lost. So, let us take a person with no information about the going price of the Nvidia GeForce FX 5200 video card (for now, imagine the user wants this exact card—perhaps it was recommended by their nephew or reminds them of their high school sweetheart). Before the Internet, the person would have had to travel to a number of different stores or purchase a catalog to find the going prices. Let’s say that this person is a perfectly average Farm Equipment Mechanic, earning $13.72 per hour,10 who drives a 2004 Dodge Ram 1500 Pickup, getting 17 mpg highway.11 If this person checked 4 stores, which took 4 hours and required driving 20 miles, the cost would have been (4 hours * $13.72 per hour) + (20 miles / 17 mpg * $2.00/gal), or $57.23, just to find and compare prices at four stores. If they instead had bought ($3.50) and perused a computer catalog, they would probably be able to read it cover to cover in just three hours, making the cost $44.66 to find and compare prices from perhaps 10 retailers. We should also state here that we are assuming this person derives no entertainment value from this endeavor – for our subject computer peripheral shopping is a grim duty.
Would our subject, being a rational actor in a market economy, actually do the above? pricewatch.com lists prices ranging from $43.00 to $67.00. So potentially, shopping around could save our subject $24.00, leaving a net benefit of -$33.22 or -20.66. Unfortunately, our subject cannot know this before hand, so perhaps this time he does it, realizes that his shopping around has in the end cost him, and resolves to never do so again.
One month later our same subject has ruined his video card in a tragic milkshake accident but has begun using the Internet. This time, he decides to shop online. He types in “www.some_price_aggregator.com,” types “GeForce FX 5200” into the search box, and finds the price range listed above at 122 different retailers. This has online taken him about 15 minutes, and let’s say a total of 30 minutes one he has completed his purchase. This has possibly saved him $24.00 at an opportunity cost of $6.86, leaving a net gain of $17.14. At this rate, his DSL connection (which we have assumed he would have purchased anyway, like his truck) will pay for itself. If everyone was like our subject, retailers would be forced to sell as close as possible to the minimum of their average total cost, instead of jacking up the price and taking some of the consumer surplus by leveraging ignorance. Total benefits are maximized, and all is right in the world.
But wait—our man has second thoughts. Drunk with his newfound power, he noticed the user reviews of the retailers. Let’s say that each retailer has an average of 5 user reviews, and that enough of them say “don’t buy from this shop, it’s a scam, they’ll steal your identity!” that or subject reads them all for the lowest 10 prices. At 5 minutes per review and 50 reviews, that’s 4 hours and 10 minutes, or $57.17. He has now lost $33.17, but has avoided the $652 average cost of dealing with identity theft.12 Or has he? Would he have been at risk simply going to the closest retailer in his neighborhood and paying the $67.00 maximum price?
Sure, some_price_aggregator.com may implement new features that drastically reduce searching times. But even if perfect price and credibility information can be made available instantaneously to all customers, this whole example abstracts away the types of information where sellers have a huge advantage over buyers—domain knowledge. A person or firm that sells video cards not only knows about the GeForce FX 5200, but the 5600, the GeForce 6600 GT AGP 128MB, and the various other manufacturers as well. It is the seller’s job to know all about the merchandise every single day, whereas most buyers of video cards only look at them once every few years when they upgrade their computer. How much time does it take out subject to figure out he needs AGP rather than PCI, or how many hardware pixel shaders he should budget for? The Internet both dramatically cuts down the time needed for buyers to educate themselves on specific issues and dramatically increases the amount of information available to wade through. This is not to say everyone is lost in a sea of uncertainty, Googling in vain. Most likely, the seller simply does not know how much they do not know. At some point the time investment will rise or the level of interest will fall to a point where it is no longer worth it and the buyer will just make a purchase. Even with the amazing powers of the Internet, this will fall somewhere below the market’s total benefits.
This is not the Internet’s fault. The very idea of perfect information is an abstraction, and really not possible—entropy and the Second Law of Thermodynaimcs tell us that all information transmission must eventually lose information. But really, who has time to worry about the heat death of the universe when there are video cards to buy? It is interesting, though, that perfect information is one of the key characteristics of a perfect market, simply because it’s impossible and if it were possible, what would stop, say, command economies from taking advantage of it as well?
Summary and Conclusions.
If the Internet is indeed bringing the market economy closer to perfect information and therefore perfect competition, we should be able to see some results. In the long run, economic profits in perfectly competitive markets will be zero, leaving normal profits. Firms will produce where marginal cost equals price and where their average total cost is at a minimum. A complete statistical analysis of the many industries now participating in the market online is beyond the scope of this paper, but there is some evidence that goods bought and sold online are moving toward commodity pricing. Products as diverse and complicated to manufacture as computer RAM20 and digital cameras21 have at least been called commodities by industry commentators.
Information products, although widely sold online and often subject to seller aggregation web sites, do not seem to be facing the same pressure, except perhaps in the used market.22 One major factor is that intellectual property laws confer artificial scarcity to goods and monopoly to sellers. The market for information goods can at best be monopolistic competition, assuming IP laws continue to protect more kinds of information for longer and longer periods of time.
Although the online marketplace in general, and price aggregation websites in particular, have had a dramatic effect on how buyers gather information, it is clear that no amount of networking will allow buyers to break out of basic economic laws.
Works cited
9 Connor-Linton, Jeff. “Chi Square Tutorial” Georgetown Linguistics. 22 March 2003. <http://www.georgetown.edu/faculty/ballc/webtools/web_chi_tut.html> (2 May 2005).
10. U.S. Department of Labor, Bureau of Labor Statistics. “Occupational Employment Statistics – 49-3041 Farm Equipment Mechanics.” November 2003. <http://www.bls.gov/oes/current/oes493041.htm> (2 May 2005).
11. U.S. Department of Energy. “Find a car.” 2004. <http://www.fueleconomy.gov/feg/findacar.htm> (2 May 2005).
12. Mohl, Bruce. “Providers push insurance covering theft of identity: Skeptics say fears trump facts.” The Boston Globe. 6 February 2005. <http://www.boston.com/business/articles/2005/02/06/providers_push_insurance_covering_theft_of_identity/> (2 May 2005).
13. Gray, Robert M. Entropy and Information Theory. New York: Springer-Verlag 1990. pp. 14-16.
20 Gain, Bruce. “DRAM Prices and Pork Rind Futures.” Tom’s Hardware Guide. 28 August 2003. <http://www.tomshardware.com/business/20030828/> (2 May 2005).
21. Virata, John. “Concord 5340z Digital Camera.” Digital Media Designer. 2005. <http://www.digitalmediadesigner.com/articles/viewarticle.jsp?id=31384> (2 May 2005).
22. Lorek, Laura. “Used Stuff Sells Well Online.” Interactive Week. 25 February 2001. <http://corp.half.ebay.com/pressfiles/zdnet_02_25_01/0_4164_2.htm> (2 May 2005).