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Bar Journal - March 1, 2001

Competition Policy in the E-Commerce Marketplace

By:
Will the Economics of the Information Age Foster More Monopolies and Should Anyone Care?

INTRODUCTION

Competition regulation in the information age, particularly in the form of the vigorous federal antitrust enforcement efforts aimed at Microsoft Corporation, has been both heralded and excoriated by the public and supposed experts in economics.1  As companies around the world struggle to wean themselves from industrial age methods of competition and develop effective business models to survive and thrive in the ever-evolving information age economy, there is an equally important struggle to forge new rules for antitrust enforcement and competition regulation of this increasingly important e-commerce marketplace.

Even before the emergence of the information age economy and before e-commerce was a common term of usage, providing antitrust guidance to clients was a difficult and uncertain affair. Now, with the e-commerce economic engine driving an unprecedented period of prosperity and growth some have called into question the basic economic assumptions that underlay antitrust enforcement policies that grew out of the experiences of the industrial age.2  This reexamination of the economic principles that have formed the foundation of competition policy for so many years can only further complicate the task of providing e-commerce clients with effective antitrust counsel.

To cite but one example, consider two speeches, given a day apart in May of last year, both made by Clinton administration officials who both happened to be visiting the epicenter of the new economy, Silicon Valley. Joel Klein, at the time the Assistant Attorney General for Antitrust, was defending his organization’s pursuit of Microsoft, one of the dominant information age businesses. When reflecting on the application of antitrust policies developed to deal with industrial age issues Klein had no hesitation. According to Klein, "The core principles of antitrust reflected in the Sherman Act, like other fundamental principles embodied in venerable texts like the Constitution and the Bill of Rights, should not be changed in this new era."

Only one day later then Treasury Secretary Lawrence Summers was delivering quite a different message only a few miles away. Summers, capturing some of the economic thinking postulated by Joseph Schumpeter nearly a half century earlier,4  was less troubled by Microsoft’s dominance of PC operating systems. In fact, Summers argued that the pursuit of such dominance was a positive force, not something to be punished. As expressed by Summers, "The only incentive to produce anything is the possession of temporary monopoly power—because without that power the price will be bid down to marginal cost and the high initial fixed costs cannot be recouped. So the constant pursuit of that monopoly power becomes the central driving thrust of the new economy. And the creative destruction that results from all that striving becomes the essential spur of economic growth."

The question of who is right or wrong in their interpretation of the Microsoft case is sure to be the subject of many debates; from the halls of academe, to global boardrooms, and even to the local pubs. No doubt the Supreme Court of the United States will have the final say over the fate of Microsoft, but there is nagging suspicion in many quarters that "something is different" about the economics of e-commerce. Perhaps Secretary Summers was most prescient in his observation that "the right metaphors for the new economy are more Darwinian, with the fittest surviving, the winner frequently taking all, and, as modern Darwinians have come to understand, accidents of history casting long and consequential shadows."6 

This article will explore the possibility that the economics of many information age markets may foster self-organizing monopolies, in contrast to most industrial age markets in which monopolies are rare and are usually obtained or maintained through unfair or coercive.

SELF-ORGANIZING SYSTEMS

Ever since Darwin the notion of self-organizing systems in biology has gained nearly universal acceptance. In biological terms a self-organizing system, like a flock of Canadian geese flying in perfect unison or school of fish darting and weaving among the coral as one, unites the disparate, independent actions of individuals into a complex and coherent whole without centralized command and control. The individuals, following simple "rules", develop structures and behaviors that were not those necessarily intended by the individuals. The geese flying in formation are not obeying the directions of a leader, but are simply following certain basic flight rules. Each individual seeks out a spot where the vortex of air from another goose lessens that individual’s aerodynamic load and thus makes flying easier. The result is the recognized "V" formation. And, if one closely observes geese in flight, one notices that the "leader" changes periodically. Because the lead goose does not have the benefits of following in the vortex of another goose, and tires more quickly than the others in more favored positions, the "leader" is replaced by a bird who has been conserving energy by flying farther back in the flock.8 

Humans often insist that "someone" or "something" must be controlling and directing the organization and operation of orderly, complex, and interacting systems.9  But recently, an awareness of how decentralized systems can also form orderly, complex aggregations and interactions without centralized command and control has emerged; first in biology10 , now in economics11  and even in the production of digital domains.12  As our understanding of these "self-organizing, chaotic13  phenomena" increases the implications for policies and strategies to modify and direct outcomes are profound.14 

The reason that free market capitalism has thrived is that it self-organizes to produce, at least in comparison to alternatives, beneficial results.15  In the industrial age economy, the decentralized ideal of the capitalist model works, for the most part, because when individuals, pursuing selfish interests (like the goose seeking an easier flying burden), interact freely in the marketplace the resulting complex and ordered system produces benefits that exceed its costs. On ethical rather than economic terms, this self-organizing free market satisfies three moral criteria: 1. justice (distributional justice under the capitalist criterion whereby each receives according to contribution and according to voluntary bargained-for exchange), 2. rights (right of free consent, voluntary exchange, and freedom of choice), and 3. utility (resources are allocated, used and distributed efficiently).

We can find further evidence of our acceptance, and even embrace, of the self-organizing nature of the free market economy in antitrust law enforcement, which seeks to preserve, protect and promote what we understand to be the best economic system. A primary tenet of antitrust enforcement is that prices in the economy should be developed on a decentralized rather than a centralized basis.16  Centralized price determination is reserved for the government when it is determined that a market failure (such as a "natural monopoly") has occurred - as in the case of utility rate regulation.17 

There is no doubt that a truly free market economy is a self-organizing system. By following the simple rules of individual self-interest the collective interactions in the free market produce a dynamic and complex economy that answers the four basic economic decisions18  in a manner superior to command and control systems. Many have argued19  that the internet should be left alone, and that a rough and tumble free market will produce that best outcomes in terms of efficiency and consumer benefits. The operation of the free market in the industrial age has had this effect so why not apply the hard-won lessons of the industrial age to the information age?

POTENTIAL FOR SELF-ORGANIZING MONOPOLIES

The question posed is whether the economic environment that is emerging in the information age, particularly e-commerce on the internet, is sufficiently different from that which prevails in most of the industrial age sectors, that the same self-interested behavior by individuals and organizations, will lead to undesired consequences or structures where the long-term benefits might be outweighed by the costs and burdens.20  Specifically, is the environment of the internet such that the activities of individuals and organizations will self-organize into monopolistic structures? This short article examines six separate but often interrelated factors that are found in many e-commerce business sectors that are emerging in the information age economy. When one or more of the first five factors examined are present in sufficient strength it is suggested that there is the danger of self-organizing monopolistic structures, while the sixth factor examined may have a mitigating effect.21 

1. Scale economy effects

Scale economy effects occur when the fixed costs associated with the production or distribution of a product or service can be spread over a large volume of output, thereby lowering that portion of the fixed cost that would be allocated to each individual unit of output and subsequently lowering the per unit total cost. Ever since the beginning of the industrial revolution economies of scale have played an important role in determining the profitability of companies. During the industrial age the production of the typical manufactured product required a substantial amount of material and labor to produce each additional unit. This is readily understood when one considers the manufacture of an automobile. As a result, most industrial age businesses experienced a significant percentage of variable costs relative to fixed costs.22  This tempered scale economy effects and permitted multiple companies of varying sizes to survive, and indeed thrive, in various industries.

In the high-tech economy of the information age the ratios between fixed costs and variable costs have changed for many products. Now the percentage of fixed costs to variable costs can greatly exceed those common during the industrial age. Because of the high fixed costs associated with the development, production and distribution of many information age items relative to their variable costs, economies of scale are even more important today than in the industrial age and can lead to industry structures where a single firm can dominate a market by exploiting a scale economy derived cost advantage.23 

INDUSTRIAL AGE EXAMPLE

Imagine three companies each making an industrial commodity product. The first company, Company A, has an annual production of one million units. And let’s assume that the fixed to variable cost ratio in this particular industry is 30 percent for fixed costs and 70 percent for variable costs. Assume that a second manufacturer, Company B, has an annual production of 1.25 million units of the same product, and Company C has an annual production of 2 million units. All have the same percentage ratio of fixed to variable costs.

Industrial Age - 30% fixed costs, 70% variable

  Company A Company B Company C
Output 1 million 1.25 million 2 million
Fixed $300,000 $300,000 $300,000
Variable ($70 per unit $700,000 $875,000 $1,400,000
Total $1,000,000 $1,175,000 $1,700,000
Cost/unit $1.00 $0.94 $0.85

Following these assumptions the above chart illustrates the differing costs per unit the three companies face. For Company A the costs are one dollar per unit. For Company B the costs are 94 cents per unit. The company with the largest market share in the industry, Company C, with double the production of Company A, has per unit costs of 85 cents. While this 15¢ per unit cost advantage is not insignificant it is may not be competitive decisive.24 

INFORMATION AGE EXAMPLE

In many information age industries the ratio between fixed and variable costs is the reverse of that found in the industrial age situation example.25  To illustrate the point, assume that Company A now has fixed costs that are 70 percent of its total costs and variable costs are only 30 percent of its total costs. This is the opposite of the previous example. Also assume Company B has the same ratio of fixed to variable costs. If one follows the example that was used above with Company A producing one million units and Company B producing 1.25 million units one discovers that the costs per unit for Company A is still one dollar but now the cost per unit for Company B is $.86 per unit and $.65 per unit for Company C. Thus, in the information age economy a company with greater production can enjoy a significant cost advantage due to economies of scale.

Information Age - 70% fixed costs, 30% variable

  Company A Company B Company C
Output 1 million 1.25 million 2 million
Fixed $300,000 $700,000 $700,000
Variable ($.30 per unit) $700,000 $375,000 $600,000
Total $1,000,000 $1,075,000 $1,300,000
Cost/unit $1.00 $0.86 $0.65

These scale effects are even more profound if the ratio of fixed to variable costs is 99 to 1 as might be more realistic for certain web related goods where the fixed costs are substantial and the variable costs approach zero.26 

Internet Example- 99% fixed costs, 1% variable

  Company A Company B Company C
Output 1 million 1.25 million 2 million
Fixed $990,000 $990,000 $990,000
Variable ($.01 per unit) $10,000 $12,500 $20,000
Total $1,000,000 $1,002,500 $1,010,000
Cost/unit $1.00 $0.80 $0.51

In this final example the cost advantage of Company C, with double the output of Company A, has gone from 15¢ in the first industrial age example to a more competitively decisive 49¢ in this scenario. In markets where consumers are price sensitive this can be a source of significant market power.

2. Learning/experience effects

Learning curve and experience curve effects express the mathematical relationship between the accumulated output of a product at the unit costs of the product. The effects are thought to be underlying natural characteristics of organized activity and have long been observed in industrial age industries.27  The relationship is generally expressed in terms of a percentage decline in cost for each doubling of output. For most standardized manufacturing industries cost declines of 10 to 30% are common.28 

Learning curve and experience curve effects are related but slightly different concepts.29  Learning curve effects were first observed in the manufacture of aircraft prior to World War II30  and have been subsequently documented in a large number of industries.31  The effect has also been retroactively applied to analysis of historical manufacturing data.32  To be precise, the term learning curve effect applies to the decline in manufacturing costs as output increases whereas the term experience curve effects is slightly broader and is used to describe the decline in total costs as output increases. For purposes of this article the term learning curve will be used to describe both effects, although the reader is reminded to keep in mind the differences.

Unit Costs for Three Learning Curve Effects

Cum. Output in Thousands Unit Cost with 90% Learning Curve Unit Cost with 80% Learning Curve Unit Cost with 70% Learning Curve
1 $1.00 $1.00 $1.00
2 $0.90 $0.80 $0.70
4 $0.81 $0.64 $0.49
8 $0.73 $0.51 $0.34
16 $0.66 $0.41 $0.24
32 $0.59 $0.33 $0.17
64 $0.53 $0.26 $0.12
128 $0.48 $0.21 $0.08
256 $0.43 $0.17 $0.06
512 $0.39 $0.13 $0.04

The chart above lists the unit costs for three different learning curves (90%, 80% and 70%) for a series of cumulative outputs. Referring to the chart, if Company A has a cumulative output of 2,000 units and is in an industry with a relatively modest learning curve effect of 90% the unit costs for Company A will be $.90. If Company B in the same industry has cumulative output of 512,000 units the per unit costs for Company B will be $.39. This puts Company A at a $.51 per unit cost disadvantage when competing in the market with Company B. This means that Company B can sell its product for $.75 per unit, which will yield a substantial per unit margin of $.24. This price, with which Company B is happy, is below the costs of Company A and should result in the exit of Company A from the marketplace. At the same time new entrants are facing $1.00 per unit costs and are deterred from entry.

The analysis is even more devastating for Company A if the industry has a 70% learning curve effect. In that situation Company B (with the 512,000 cumulative output) will have unit costs of $.04 while Company A has unit costs of $.70 for a substantial $.66 per unit cost disadvantage. Again, Company A will be driven from the marketplace without predation or any specific anti-competitive or restrictive conduct undertaken by Company B.33 

It has been suggested that learning curve effects are even more pronounced in knowledge and technology intensive industries.34  In addition, many information age products have extremely low (or potentially no) marginal costs so accumulation of output can be accomplished at little or no expense.35  To the extent that learning curve or experience curve effects play a significant role in information age industries there is a marked tendency to favor the first mover, the company that is able to accumulate output quickly.36 

3. Superstar effects

Superstar effects37  are related to the scale economy effects but differ in important aspects. In times past there were limits on the capacity of individuals or firms to satisfy the demand for their products or services. As a consequence, after the capacity of the most desired supplier had been reached customers would, of necessity, turn to their second best choice. This excess of demand over supply would also have the effect of permitting the suppliers of the preferred product or service to charge a higher price. This again would have the effect of customers shifting to their lower-tiered choices.

Additionally, if, in an effort to increase capacity to satisfy the unmet demand, the preferred or first choice supplier experienced increased variable costs there would be a point where the product or service cost would rise and demand would lessen with the result that customers would again shift to less desirable, but cheaper, alternatives. If variable costs are a significant portion of the total costs then the cost rise will be greater than if the variable costs are a much smaller percentage. For example, in the nineteenth century an entertainer was capacity constrained by the size of the performance venue (the seating capacity of the theater). The wealthy and privileged would have access to the most preferred entertainers, but most of society would not.

As a result, many less-talented individuals were able to make a living as entertainers, going from town to town and performing at less desirable venues. The choice for the audiences in the lower tier venues was to listen to a less-desired entertainer or none at all. This situation permitted the second, third and lower choice performers to maintain a market presence.38  With the new information technologies audiences in lower tier venues no longer need to settle for lesser talent. They can have the most desired entertainment since it can be provided (by electronic and digital media) with no marginal cost consequences to the entertainer.

Unlike scale economies and learning curve effects, superstar effects are based on specific consumer preference (other than favorable prices which can result from the scale and learning effects) for the perceived "best" product. As a consequence, the fact that a winner-take-all marketplace may arise due to superstar effects may not necessarily be bad for the consumer since in such a winner-take-all marketplace each consumer can have the most desired product or service and need not settle for second or third choices.39 

4. Network Effects

Network effects or network externalities40  exist when the amount that one is willing to pay for access to the network is dependent upon how many other parties are also connected to the network.41  Network products or services become more valuable as their use becomes more widespread.42  Fax machines, telephones and the internet are all prime examples of products with significant network effects. The existence of network effects has also become decisive in antitrust enforcement43  and has even been the source of a cautionary warning from the Federal Reserve regarding electronic cash systems.44 

As more and more users join the network, there is an increase in the network’s value. Often the network participants will tend to settle on a single technology as a standard. This technology choice can then become self-perpetuating,45  despite the emergence of a subsequent superior technology.46  This phenomenon is sometimes referred to as "lock-in" and results in path dependency.

STANDARDIZATION

Standards are often required to allow the efficient functioning of a network. As a consequence, achieving a critical mass of acceptance is significant in a number of information age markets. The first firm to achieve a critical mass of acceptance sets the de facto standard, and success then breeds more success. When a critical mass is reached on a standard, the beneficiary of the standard receives increasing benefits as more and more individuals switch to the dominant standard, which as a result increases the standard-setter’s dominance.47  The importance of first mover advantages may go beyond critical mass of acceptance. First movers will also be farther down the learning curve, and may enjoy greater scale economies.48 

5. Information Search and Retrieval Burdens

The fifth factor contributing to self-organizing monopolistic structures in the information age focuses on the burdens of information search and retrieval. This stems from two causes. First is the complexity of the products and services. The informational asymmetry between buyers and sellers is magnified in technology driven markets. Individual consumers are often ill-equipped to comprehend the salient technological features of competing products and systems (is Betamax better than VHS?). As result, consumers place increased reliance on reputation and prior experience to make judgments. A type of herd behavior can evolve, further entrenching market leaders. It is safer to stay with the grazing herd, even if the herd is grazing in a sub-optimal area. Any individual in the herd could go to a more optimal grazing area but only at the risk of leaving the safety of the herd. As was aptly stated in the early stages of the information age regarding computer purchases, "No one ever got fired for buying IBM."49 

The second cause of the information search and retrieval burden is a direct by-product of the information age. The increasing amount of information available can overwhelm even the most conscientious consumer.50  Who among us truly knows whether or not our long-distance carrier is currently the cheapest? All the data to make this determination are easily obtained but few of us go to the bother. Even if we did make the effort to collect and process the information at the time of the initial purchase decision, it is less likely that the decision will be regularly revisited. In such an environment established, recognized trademarks and repeat customers can be significant sources of competitive advantage that contribute to aggregation.

6. Non-rivalry and Reproduction Costs

Like Pandora’s box our story ends with one new factor of the information age economy that may provide a ray of hope against self-organizing monopolistic structures, although this characteristic poses ethical and economic dilemma of its own. One of the fundamental characteristics of tangible property in the industrial age economy is that possession is rivalrous. If I am in possession of a car you cannot be in simultaneous possession of the same vehicle. The same cannot be said for knowledge and information based property. Digital property is non-rivalrous. This final characteristic of many emerging information age markets is different from the prior five in that does not appear to contribute to the formation of self-organizing monopolistic structures. In fact, the non-rivalrous nature of many knowledge, information and data products may actually hinder the evolution of monopolistic structures in the information age economy, or at least temper their social costs.

The reproductive ease associated with knowledge and information products can make it more difficult for a monopolist to extract monopoly rents once market dominance is achieved. So consumers may first benefit from the competition among firms to succeed in the winner-take-all marketplace, and then may find themselves further benefiting from the inability of the "winners" to extract monopolistic prices. Unfortunately, there is a downside.

When the possibility of non-rivalrous possession is coupled with the costs of reproduction a serious problem arises. In the industrial age economy social welfare was maximized because consumers were willing to pay a price for tangible goods that was greater than the marginal cost of producing another copy. It was unlikely that you were going to cheaply "clone a copy of your Ford" for a friend. The marginal cost of reproduction (often near zero) for many digital goods is below the marginal cost of producing and distributing the product. Will anyone have an incentive to produce digital goods where the costs of production and distribution exceed the marginal cost of reproduction? If the answer is no, all of society will be worse off. The producers of digital goods have begun to attack the situation by trying to increase the marginal costs of reproduction through the threat of legal prosecution for infringement or through technological changes (such as digi-marking).51 

CONCLUSION

The self-organized monopolies that may arise in the information age economy appear to pose an ethical and regulatory dilemma that was not present in the industrial age economy.52  As noted in the beginning the industrial age economy satisfies three moral criteria.53  The potential winner-take-all nature of the many information markets can cause a disassociation between these three moral criteria.54  Distributional justice may be threatened in that rewards may exceed one’s contribution. In addition, individual rights of choice may be limited by the absence of competitive alternatives. On the other hand, one could argue that utility is actually enhanced as costs are driven to their lowest levels. Of course, low costs do not guarantee low prices, so the benefits of the effects listed above may be captured and internalized by the producers rather than shared with the consumers.

The possibility for self-organizing monopolies to evolve in these winner-take-all markets also makes them extremely attractive because of their potential remuneration for the winners. As a result participants can become engaged in an expensive "arms race" to achieve dominance. This type of competition can result in escalating expenditures that may not produce any additional security of success since security of success is relative to the threat.55 

In addition, the perceived rewards of winner-takes-all markets attracts significant entry. Since most of these entrants will fail in a winner-take-all market there is a danger of resource waste due to over investment (and subsequent failure of investments made by the market losers). It still may be a rational investment choice to enter a winner-take-all market even if the probability of being the winner is relatively low. For example, suppose there are ten companies vying for dominance in industry A. Further assume that one of the ten will eventually achieve dominance and the others will ultimately fail. If the rewards are more than 10 times the potential investment cost of competing then the companies will rationally choose to "play the game" even though 90% of them will ultimately fail.56

In contrast, in most industrial age markets the rewards are roughly comparable with effort. Principles of justice require that equals are treated equally and non-equals non-equally. Justice requires a proportionality of effort to reward. Someone who works 20% harder should receive 20% more rewards. A company that is 10% more efficient should receive 10% more rewards. In these winner-take-all markets the effort/reward proportionality may not be maintained. A company that is 10% more efficient and achieves dominance may receive a vastly larger reward.

As a final note, one might ask what should or can be done about this increased potential for self-organizing monopolies in the information age. Some look to renewed vigor in the enforcement of competition laws.57  Marketplace competition and consumer choice has long been a powerful method to check firm power without the need for command and control structures in the economy. If you don’t like what I am selling you can just go down the street. But, there will have to be conceptual changes for the antitrust laws to be effective. The current concept of illegal monopolies in our legal system seems to assume a centralized model.58  The competition laws do not prohibit monopolies but the act of monopolizing. Hence, there is a search for the evil monopolist and a need for demonization to justify enforcement action.59  A "monopolizing act" assumes doing something "wrong" or coercive (maliciously interfering with competitors, cabals gathering in smoke filled rooms to divide markets and fix prices, forcing consumers to buy products they don’t want to get others, and so on). In the self-organizing system that characterizes most of the industrial age free market economy, perhaps it was only the anomalous situation that resulted in a monopoly. And perhaps, it took "an extra push" from a amoral monopolist bent on subverting competition to achieve or maintain a monopoly. But it is suggested if the economic forces that are described in this article are present in sufficient strength that this model may not hold in many information age markets.

If this is so, then what? The answer is not to substitute centralized control for the freedom of the market. Instead we need to better understand the dynamics of the system. A closer examination of the environmental rules that are favoring the self-organizing monopolistic structures is required. Armed with this knowledge we can selectively try to change the rules. For example, the network effects of "owning" an industry standard could be addressed.60  Perhaps we can also draw lessons from biological self-organizing systems where randomness and fluctuations are important to progress. Businesses, and business clients, like stability and predictability. Perhaps surprise, challenge and instability are positive forces in a dynamic, non-linear environment, and as counselors to businesses information age attorneys will need to help guide them through this uncertainty.

ENDNOTES

49.
1. Prepared Testimony of Jonathan B. Baker Washington College of Law American University, Before the House Committee on the Judiciary on the Subject - Oversight Hearing on the Antitrust Enforcement Agencies, April 12, 2000.
2. Laura D’andrea Tyson, Though It’s A New Economy, It’s Got Some Old Flaws, Business Week, January 10, 2000, P. 32.
3. Robert Hahn, Old-Fashioned Trust-Busting in the New Economy, The Washington Post, May 25, 2000, p. A37.
4. Schumpter argued that economies grew through a process of what he termed "creative destruction" whereby old methods were pushed aside in a dynamic process of change. Joseph A. Schumpter, Capitalism, Socialism, and Democracy (3rd ed. 1950)
5. Hahn, op. cit. p. A37.
6. Id.
7. In the early 1970’s Professor Keller at MIT demonstrated that slime mold cells, a simple life form without specialized cells, formed clusters or aggregations simply in response to a chemical secreted and sought by each slime mold cell. This "aggregation without a leader" is but one example of self-organizing behavior whereby complex structures emerge as the result of simple interaction "rules" followed by free acting individual organisms. [These experiments were conducted by Evelyn Fox Keller, a professor of mathematics and humanities whose work has been in mathematical biology and in the history, philosophy, and psychology of science]
8. Likewise, the almost magical coordination of schooling fish results from a simple desire in each fish to be at the center of a group of fish where that individual fish is safest from predators. As the school moves away from any individual fish that single, simple rule (get to the center quick) orchestrates the movement of the individuals into a cohesive whole and the school swims as one. One could image a different system for coordination with each fish having a communication device and a leader transmitting information to each fish to choreograph a turn. One can appreciate the simplicity and efficiency of the self-organizing system in comparison.
9. Although the self-organizing nature of biological systems is widely accepted (as noted earlier) there are some who hold to a command and control explanation of biology. This disagreement is at the core of the creationism debate. Our tendency to centralized control explanations may also help explain the persistence and popularity of conspiracy theories. See also, Michale Resnick, Changing the Centralized Mind, Technology Review, July 1994.
10. Benno Hess and Alexander Mikhailov, Self-organization in living cells, Science (4/8/94) at 223. Howard T. Odum, Self-organization, transformity, and information, Science (11/25/88) at 1132.
11. Larry D. Browning Janice M. Beyer Judy C. Shetler, Building cooperation in a competitive industry: SEMATECH and the semiconductor industry, 38 Academy of Management Journal 113 (1995); Peter Nijkamp and Aura Reggiani, Non-linear Evolution of Dynamic Spatial Systems: The Relevance of Chaos and Ecologically-Based Models, 25 Regional Science and Urban Economics (April 1995); Raghu Garud and Suresh Kotha, Using the Brain as a Metaphor to Model Flexible Production Systems, 19 Academy of Management Review 671 (1994); Friedrich Hinterberger, Self-Organizing Systems, appearing in The Elgar Companion to Austrian Economics, Peter J. Boettke, ed. (Ashgate, Brookfield, Vt, 1994); and, Michael J. Radzicki, Institutional Dynamics, Deterministic Chaos, and Self-Organizing Systems, 24 Journal of Economic Issues (March 1990)
12. Michael Rothschild, Call It Digital Darwinism, Upside, December 1991. 20,000 bytes under the sea, Economist (6/13/98) at 81. See also, M. C. Yovits and S. Cameron, Eds., Self Organizing Systems (Pergamon, New York, 1960); H. von Forster and G. W. Zopf, Eds., Principles of Self-Organization (Pergamon, New York, 1961).
13. The term chaotic is not used in its popular sense but to describe non-linear dynamic systems. Chaos theory posits that non-linear dynamic systems are highly responsive to initial conditions. In a self-organizing, chaotic marketplace small initial advantages (first mover, slightly better technology, higher visibility) can lead to enormous rewards.
14. The Sante Fe Institute in New Mexico has become a center for research in this area.
15. For a discussion of this point see A. Michael Froomkin and J. Bradford De Long The Next Economy? at http://www.law.miami.edu/~froomkin/articles/newecon.htm
16. According to the Supreme Court a freely determined price is the "central nervous system of the economy," [United States v. Socony-Vacuum Oil Co., 310 U.S. 150, 226 n. 59 (1940)] and an agreement that "interfere[s] with the setting of price by free market forces" is illegal on its face. [United States v. Container Corp., 393 U.S. 333, 337 (1969)]
17. "A natural monopoly occurs when, because of the high ratio of fixed costs to variable costs, a single firm has declining average costs at the level of demand in the industry, such that the single firm can supply the service more cheaply than two firms could. United Distribution Companies v. Federal Energy Regulatory Commission, 88 F.3d 1105 (D.C.Cir. 1996) at fn 4 citing Richard A. Posner, Economic Analysis of Law §12.1, at 343-45 (4th ed. 1992) For another antitrust case where the natural monopoly nature of utilities was explicitly recognized by the Supreme Court see Otter Tail Power Company v. United States, 410 U.S. 366 (1973). A natural monopoly has positive supply-side network effects due to scale economies.
18. The four fundamental economic decisions that must be made by a society are: 1. What products to produce. 2. How much of each to produce. 3. What resources shall be used in producing these products. 4. Who will get what. Or to express the four in a single sentence -Who will produce what and how for whom?
19. John Perry Barlow, Selling Wine Without Bottles: The Economy of Mind on the Global Net, http://www.eff.org/pub/Publications/John_Perry_Barlow/idea_economy.article, and John Perry Barlow, Stopping the Information Railroad, Keynote Address, Winter 1994 USENIX Conference, San Francisco, California, January 17, 1994 at http://www.eff.org/pub/GII_NII/info_railroad_usenix_barlow_eff.speech. The freedom from control and regulation is often part of the desire for preservation of the freedom of speech on the internet. See for example, the web site of Internet Freedom at http://www.netfreedom.org/uk.
20. The fact that something is different about information age competition, and the internet in particular, has not escaped notice. According to one commentator, "Something very unusual is going on here. … There is something about the information industry in general and the Internet in particular that makes the application of normal antitrust rules problematic, whether you approach them from the point of view of classical antitrust scholarship or of the Chicago School." Mark A. Lemley, Antitrust and the Internet Standardization Problem, 28 Conn. L. Rev. 1041 (1996)
21. Some authors have characterized the "new" economics of the information age as the proliferation of winner-take-all markets. Robert H. Frank and Philip J. Cook, The Winner-Take-All Society, (Free Press, 1995)
22. Variable costs are those that vary with each unit of output such as labor, raw materials, energy, and shipping. Fixed costs, on the other hand, remain unchanged or fixed, regardless of the number of units produced and include land, plant and equipment
23. For a discussion of this point and its application see Joseph Kattan, Market Power in the Presence of an Installed Base, 62 Antitrust L.J. 1 (Summer 1993)
24. One can see an example of this in automobile manufacturing. Although General Motors for many years enjoyed greater scale economies than Ford or Chrysler, the cost advantage was insufficient to be competitively decisive and both Ford and Chrysler were able to effectively compete in the marketplace.
25. For a discussion of scale economy effects (among others) in innovation markets see William E. Cohen, Competition and Foreclosure in the Context of Installed Base and Compatibility Effects, 64 Antitrust L.J. 535 (1996).
26. The development and subsequent distribution of software fits this description. With the advent of internet distribution the variable costs fall even more, since currently the packaging and shipping of software are the most significant variable costs.
27. Wilfred B. Hirschmann, Profit from the Learning Curve, Harvard Business Review, January-February 1964. The first documented observation of the learning curve effect was made in 1925 by the commander of what is now the Wright-Patterson Air Force base in Ohio.
28. Pankaj Ghemawat, Building Strategy on the Learning Curve, Harvard Business Review, March-April 1985. The unit cost declines of 10% and 30% for each doubling of output are generally described as 90% and 70% learning or experience curves, respectively.
29. For a more complete discussion see William J. Abernathy and Kenneth Wayne, Limits of the Learning Curve, Harvard Business Review, September-October 1974
30. Wilfred B. Hirschmann, Profit from the Learning Curve, Harvard Business Review, January-February 1964.
31. Ranging from facial tissue to computer chips. Pankaj Ghemawat, Building Strategy on the Learning Curve, Harvard Business Review, March-April 1985.
32. Application of learning curve analysis to the production of Model T and Model A automobiles by William J. Abernathy and Kenneth Wayne, Limits of the Learning Curve, Harvard Business Review, September-October 1974. The authors also discuss the dangers of strategic reliance on learning curve effects.
33. In such a marketplace the question of predatory pricing becomes more complex. Currently, the legal test for predatory pricing has two parts: (1) pricing below some "appropriate measure" of costs (not yet defined by the Supreme Court), and (2) a dangerous probability of recouping the investment in below-cost pricing. Brooke Group, Ltd. v. Brown & Williamson Tobacco Corp., 509 U.S. 209, 222-24 (1993).
34. A. Michael Spence, Competition, Entry, and Antitrust Policy, Strategy, Predation, and Antitrust Analysis 45, 65-66 (Steven C. Salop ed., 1981). One way of summing up the learning curve effect is "practice makes perfect". In information age industries where flexibility and willingness to change are present the benefits of learning curve effects should be significant. Additionally, some have argued that the more complex the undertaking the greater the rate of learning. [Wilfred B. Hirschmann, Profit from the Learning Curve, Harvard Business Review, January-February 1964] As a consequence, in high-risk, high-reward winner-take-all markets any incremental benefits, such as those from a learning curve effect, may be sufficient to determine the winner. Another author claims that "self-organizing systems are learning systems". David H. Freedman, Is Management Still a Science? Harvard Business Review, November-December 1992
35. In most tangible products diminishing returns eventually limit the positive cost effects of the learning curve.
36. This may also help explain why market share is profitable and why pursuit of market share is a rational strategy for many organizations. In the 1970’s and 1980’s the Boston Consulting Group used the learning curve in support of strategies seeking significant market share positions. John S. Hammond III and Gerald B. Allan, Note on the Boston Consulting Group Concept of Competitive Analysis and Corporate Strategy, Harvard Business School Note #175175, 1983. Learning curve effects have also been used to explain some of the results from the PIMS (Profit Impact of Marketing Strategy) database which show a correlation between market share and profitability. Robert D. Buzzell, Bradley T. Gale, Ralph G.M. Sultan, Market Share - A Key to Profitability, Harvard Business Review, January-February 1975.
37. For a general discussion of the concept see When Winners Take All, The Economist, November 25, 1995 at 82. Other discussions on the topic can be found on the web at http://www.adm.duke.edu/alumni/dm13/silver.html and http://www.gsm.cornell.edu/NewIdeas/PressReleases/WinnerTakeAll.html
38. And maintain a living wage. It is this concern over wage inequality in winner-take-all markets that is addressed by Robert H. Frank and Philip J. Cook, The Winner-Take-All Society, (Free Press, 1995).
39. If there are significant entry barriers this elimination of lower-tiered competitors may increase the riskiness inherent in the market. If the "superstar" winner subsequently becomes less desired the concentration of decision making in fewer hands may result in sub-optimal results. (All your eggs in one basket problem.) Markets with numerous competitors are more robust than single firm marketplaces, even if the single firm is currently the most desired or lowest cost producer, because of the risk posed by a single firm’s mistake is more easily corrected by consumers shifting to competitive products in a contested market.
40. Technically, network effect should be used to describe situations where there are increasing returns as the number of network participants increases and network externalities should be limited to situations where the network effect creates less than optimal conditions where a decision maker does not bear the full costs of his or her decision. S. J. Liebowitz and Stephen E. Margolis, Network Externality: An Uncommon Tragedy, 8 Journal of Economic Perspectives 133 (1994).
41. Nicholas Economides, The Economics of Networks, 14 International Journal of Industrial Organization (March 1996).
42. Economists refer to this as increasing returns. In the physical world one could think of this as a virtuous circle, where feedback from the growth becomes self-reinforcing.
43. Network externalities were cited as a significant factor in the December 1997 FTC order requiring partial divestiture in the merger of CUC International, a leading membership-based consumer services company, and HFS Incorporated, a leading franchisor of hotels, residential real estate and car rental companies. In re CUC International, Inc. (FTC, File No. 971-0087, 12/17/97)
44. "[O]nce the market attains a critical mass, growth rates may accelerate dramatically. The speed of this change will narrow the window of opportunity for curtailing negative market developments, should they arise. Hence, failure to understand the market dynamics for goods exhibiting network externalities increases the riskiness of a wait-and-see policy." William P. Osterberg and James B. Thomson, Network Externalities: the Catch-22 of Retail Payments Innovations, Economic Commentary - Federal Reserve Bank of Cleveland (February 15, 1998) available on the web at http://www.clev.frb.org.
45. This self-perpetuation is sometimes called path dependency.
46. One author claims that lock-in is particularly likely to occur when there is rapid change, information is limited, and consumers cannot foretell which technology is better or which will offer more in the future.
47. Often cited examples of this phenomenon are the well-known Betamax/VHS, Windows/Macintosh, 8 track/cassette audio tapes situations.
48. The first mover advantages may also be related to the marketplace advantages enjoyed by early or quick success in the movie and television industries.
Today the same can be said for those selecting operating systems. Microsoft Windows is the "safe" choice.
50. A similar phenomenon is beginning to appear with searches on the internet. So many "hits" are returned that an exhaustive search may no longer be effective. Automated agents and filtering mechanisms may help but there is a concern that those who control the filters (Microsoft Sidewalk is an example) could
51. Digi-marking is the electronic tagging of copyrighted work with identifying information that can assist in tracing the origin of the work. Copy protection schemes, at one time widely employed in the software market, may also reappear - and already have done so for high-end software products.
52. If self-organizing systems orchestrate the formation of undesirable structures and do so without leaders, is it fair or correct to look for culpable leaders who are the architects, the master planners, of these self-organizing structures? Is the queen termite "responsible" for the construction of the termite colony mound on the plains of Africa? No, and it is an example of the centralized mindset to even call her the "queen", which implies leadership.
53. 1. justice (distributional justice under the capitalist criterion whereby each receives according to contribution and according to voluntary bargained-for exchange, 2. rights (right of free consent, voluntary exchange, freedom of choice), and 3. utility (resources are allocated, used and distributed efficiently).
54. Some have even argued that computers are the largest driver of wage inequality in the emerging winner-take-all information age economy. By these accounts the concentration of greater economic rewards in proportionately fewer hands will lead to a substantial income and wealth gap, and since one "votes with dollars" in allocating resources in the free market economy those with more dollars get more "votes" in this resource allocation process. Whether or not this is "fair" is left for others to decide. Neil Munro, For Richer and Poorer, The National Journal, July 18, 1998. For a discussion of the moral legitimacy concerning these competitively determined profits and incomes see Derek Bok, The Cost of Talent: How Executives and Professionals Are Paid and How It Affects America (Free Press, 1993).
55. In fact the opposite may occur. If each side keeps increasing its "arms build-up" it is possible that each is less secure (or at least no more secure) than it was before the race began.
56. Expressed in decision tree format one can see that any investment up to $10,000,000 is rational, even though the likelihood of success is relatively small.
57. Even the Wall Street Journal seems to agree that the information age marketplace (or as the antitrust enforcement agencies like to call them - innovation markets) involve situations and activities, such as standard setting, network effects, market access, and new forms of competition, that can be effectively addressed by antitrust regulation. Antitrust Isn’t Obsolete In an Era of High-Tech, Wall Street Journal, Nov. 10, 1997 at 1.
58. The law also recognizes legal monopolies that are the result of "superior product, business acumen, or historic accident." United States v. Grinnell Corp., 384 U.S., at 570-571 (1966)
59. Witness the current demonization of Bill Gates and Microsoft, and the past demonization of Rockefeller and Standard Oil.
60. It is possible that the essential facilities doctrine in antitrust law could be used. Teague I. Donahey, Terminal Railroad Revisited: Using the Essential Facilities Doctrine to Ensure Accessibility to Internet Software Standards, 25 AIPLA Q.J. 277 (Spring 1997) For a discussion of the doctrine see Christopher M. Seelen, The Essential Facilities Doctrine: What Does It Mean to be Essential?, 80 Marq. L. Rev. 1117 (Summer 1997).

The Author

Professor William J. Murphy, Franklin Pierce Law Center, Concord, New Hampshire. Of Counsel, Devine, Millimet & Branch, Manchester, NN.

 

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