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«Coase’s Penguin, or, Linux and the Nature of the Firm Yochai Benkler∗ Abstract The emergence of GNU/Linux as a viable alternative to the Windows ...»

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Much of the knowledge management movement one has seen in business schools since the mid-1990s was concerned with mitigating the lossiness of managerial hierarchy as an information processing mechanism. Mitigating this lossiness is the primary job of CIOs. An example where peer production—though proprietary, not commons-based—was used precisely for this purpose was Xerox’s Eureka system for organizing the flow of questions from and answers to field technicians about failures of photocopiers. Creating a database of technician queries, capable of being answered by technicians throughout the Xerox service operations, was a way of capturing some of the lost information by implementing distributed information sharing techniques, rather than hierarchical information flows, to resolve uncertainty about specific actions by technicians. Eureka flipped the traditional conception of knowledge in a machine as codified by engineers and implemented by instruction-following technicians. The knowledge content of the machine was now understood to be something that is incomplete when it leaves the design board, and is completed over the life of the machines by technicians who share questions and solutions on a peerreview, volunteer model over a proprietary communications platform.

Recognizing the lossiness of markets and managerial hierarchies suggests a working hypothesis about why peer production has succeeded in gaining ground. Peer production may have sufficiently lower information opportunity costs as compared to markets and hierarchies, that the gains it offers as an information collection and processing mechanism outweigh the costs of overcoming the coordination problems COASE’S PENGUIN Oct. 2001 among widely distributed peers whose behavior is not mediated by price or controlled by contract.

One of the things that makes the “effort” component of an agent’s decision to act difficult to specify sufficiently to get very information-rich pricing or managerial decision-making is that individuals are immensely complex and diverse in terms of their raw abilities, focus (capacity to translate raw ability into effective action) and motivation (willingness to exert effort and focus at a given time for a given project).

All these also change not only from individual to individual, but also within one individual over time and specific external conditions. Codifying the desired attributes becomes increasingly difficult and lossy. So, for example, if the task required is very simple and routine—standing at a particular spot for eight hours and turning a knob— then the set of individual attributes necessary to specify is minimal, and an individual willing and able to perform it can be identified very efficiently through pricing or hierarchy. The passion of that same individual for Mars, and her motivation and capacity to look at Mars craters and identify them for fifteen minutes a week will likely go unappreciated and untapped in a hierarchy-based organization, and quite possibly in a price system as well. It is knowledge she may only come to possess after she has encountered the NASA clickworkers project, to which she then begins to contribute in her evenings.

The point is more general: human intellectual effort is highly variable and individuated. It is very difficult to standardize and specify in contracts—necessary for either market-cleared or hierarchically organized production. As human intellectual effort increases in importance as an input into a given production process, an organization model that does not require a standard contractual specification of the effort required to participate in a collective effort and allows individuals to selfidentify for tasks will be better at clearing information about who should be doing what than a system that does require such specification.

So, where the physical capital costs of information production are low and information itself is freely accessible (that is, where intellectual property law has not raised the price of using inputs above its marginal cost of zero), and where the cost of communication is low, individual agents can relatively cheaply scour the universe of resources to look for opportunities to invest their creative capabilities. (Their incentive to do so is any one of the indirect appropriation mechanisms ranging from pleasure to reputation etc.) Individuals can then identify both opportunities for creative utilization of the existing resources in ways not previously done,41 and opportunities to use their own talents, availability, focus, and motivation to perform a productive act. Systems that lower the cost of coordination among peers, clearing This is a point Bessen makes about complex software, see Bessen, supra, as well as a characteristic of the motivation Raymond describes as having an itch to scratch.

COASE’S PENGUIN Oct. 2001 information about what needs to or can be done, who is doing it, etc., will then enable these individuals to contribute variously-sized contributions, each of which is qualitatively better than could have been matched by markets or hierarchies. To succeed, such systems also require a mechanism for smoothing out incorrect selfassessments—as peer review does, or as, in the case of NASA clickworkers, simple redundancy and statistical averaging does. The prevalence of misperceptions as to one’s ability, and the cost of eliminating such errors, will be part of the transaction costs associated with this form of organization that are parallel to quality control problems faced by firms and markets.42 This problem is less important where the advantage of peer production is in acquiring fine-grained information about motivation and availability of individuals with widely available intellectual capabilities—like the ability to evaluate the quality of someone else’s comment on Slashdot. It is likely more important where what is necessary is a particular skill set that may not be widespread—like fixing a bug in a program.





The point here is qualitative. It is not only, or even primarily that more people can participate in production (as is sometimes said of open source development). It is that the widely distributed model of information production will better identify who is the best person to produce a specific modular component, all abilities and availability to work on the specific module within a specific time frame considered.

With enough uncertainty as to the value of various productive activities and enough variability in the quality of both information inputs and human creative talent vis-à-vis any set of production opportunities, coordination and continuous communications among the pool of potential producers and consumers can generate better information about the most valuable productive actions, and the best human inputs available to engage in these most valuable actions at a given time.

Peer production has an additional advantage relative to markets and firms, that is a function of the use that firms, and to a lesser extent market actors, make of boundaries to reduce uncertainty as to the availability of resources and agents. This advantage is cumulative to the information-processing characteristics of peer production, and relates to the size of the pools of individuals, resources, and projects engaged in information production. The same problem that creates the informational advantage of peer production—the high variability of human capital—also suggests that there are increasing returns to scale in increasing the pool of individuals and resources potentially available for use in any given production project. As explained, market- and particularly firm-based production management rely on property and contract to secure access to bounded sets of agents and resources in the pursuit of I owe thanks to Doug Lichtman for pointing out the importance of individual self-misperception as a particular potential failure of the information processing characteristics of peer production, that must be solved by these processes if they are to succeed.

COASE’S PENGUIN Oct. 2001 specified projects. The permeability of the boundaries of these sets is limited by the costs of making decisions in a firm about adding or subtracting a marginal resource, agent, or product, or the transaction costs of doing any of these things through the market. Peer production relies on making an unbounded set of resources available to an unbounded set of agents, who can apply themselves towards an unbounded set of projects and outcomes. The variability in talent and other idiosyncratic characteristics of individuals suggests that any given resource will be more or less productively used by any given individual, and that the overall productivity of a set of agents and a set of resources will increase more than proportionately when the size of the sets increases towards completely unbounded availability of all agents to all resources for all projects. The point is that even if in principle we have information as to who was the best person for a job given any particular set of resources and projects, the transaction or organizational costs involved in bringing that agent to bear on the project may be too great relative to the efficiency gain over use of the resource by the next-best available agent who is within the boundary.

Assume that the productivity (P) of a set of agents/resources is a function of the Agents (A) available to invest effort on resources (r). PA1 (Productivity of agent A1 ) is a function of set of resources A1 can work on, r1, the level of effort of A, e1, and A’s talent, (t1 ) where talent describes relative capabilities, associations, and idiosyncratic insights and educational mixes of an individual. PA increases as r and e increase, at a magnitude that is a function of t. t is a personal characteristic of individuals that is independent of the set of resources open for A to work on, but will make a particular A more or less likely to be effective with a given set of resources for the achievement of a set of outcomes. The existence of t means that there are increasing returns to making a larger set of resources available to a larger set of agents, because the larger the number of agents with access to a larger number of resources the higher the probability that the agents will include someone, Ax, with relatively high value of t, who will be more productive with rx given some ex than other agents. If A1 who works for F1 has a higher t value as regards using r2, than A2 who works for F, but r2 is owned by F2, r2 will nonetheless be used by A2 so long as the value of A2 working on r2 has a value of no less than the value of A1 working on r2 minus the transaction costs involved in assigning A1 to r2. This potential efficiency loss would be eliminated if A1 were in the set of agents who had baseline access to work on the resource set that includes r2. So, if firms F1 and F2 each has a set of agents and resources, {AF1, rF1 } {AF2, rF2 }, then PF1 + P F2 P F1+2. Furthermore, a more diverse set of talents looking at a set of resources may reveal available projects that would not be apparent when one only considers the set of resources as usable by a bounded set of agents. Finally, none of this takes into consideration collaboration, and the possible ways in which collaborating individuals can make each other creative in different ways than they otherwise might have been. Once one takes into consideration these diverse effects on the increased possibilities for relationships among individuals and between individuals COASE’S PENGUIN Oct. 2001 and resources, it becomes more likely that there are substantial increasing returns to increases in the number of agents and resources involved in a production process.43 If this is true, then in principle a state in which all agents can act on all resources effectively will be substantially more productive in creating information goods than a world in which firms divide the universe of agents and resources into bounded sets. As peer production relies heavily on opening up access to resources, for a relatively unbounded set of agents, freeing them to define and pursue an unbounded set of projects that are the best outcome of combining a particular individual or set of individuals with a particular set of resources, this largely open set of agents is likely to be more productive than the same set could have been if divided into bounded sets in firms. If the modularity of a product is insufficient to permit the aggregation of low levels of effort, and more directed incentives are necessary to induce effort, this effect might be muted relative to the importance of the application of direct incentives-based effort. In other words, the ability to link compensation to effort may be more important than the efficiency loss created by introducing a firm or market capable of inducing that incentives-based effort. But if effort/incentives can be at least partially solved by decentralization, the substantial increases in productivity born of the availability of a larger set of resources to a larger set of agents with widely variable talent endowments could be enough to make even an imperfectly motivated peer production process more productive than firms that more directly motivate effort but segment agents and resources into smaller bounded sets.

4. Integration: Problem and opportunity

This leaves us with a consideration of the last factor limiting peer production—the possibility and cost of integration of distributed efforts into a common product. It is here that the term “commons” in describing the phenomenon as “commons-based peer production,” gets its bite. Its role is to denote the centrality of the absence of property rights as a central organizing feature of this new mode of production, and to evoke the potential pitfalls of such an absence for decentralized production efforts.

What kind of commons is it, then, that peer production of information relies Commons are most importantly defined by two parameters.44 The first upon?

I am not sure there is room to formalize the relationship here on the style of Metcalfe’s Law or Reed’s Law, see David P. Reed, That Sneaky Exponential—Beyond Metcalfe's Law to the Power of Community Building, http://www.reed.com/Papers/GFN/reedslaw.html. From a policy perspective, there is no need to do so at this early stage of studying the phenomenon. It is sufficient for our purposes here to see that the collaboration effects and insights due to exposure to additional resources mean that the returns to scale are more than proportional.



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