Currently, spectrum in wireless networks is allocated using a property based scheme. This solves the problem of interference by providing coordinated access to capacity for users of multiple technologies at the cost of fixing the available capacity for each technology area. Recently, architectures have been proposed that use a cooperative strategy for capacity allocation. These have the advantage of increasing available capacity with the number of users. The author believes that cooperative wireless networks could be created that provide capacity that scales proportional to the number of users. In addition, a cooperative wireless network would have increased options with respect to Metcalfe's Law, the number of pairwise transactions that could occur would grow as N**2, and Reed's Law, the number of groups that could be formed would grow as 2**N.

The author argues that the scaling of capacity available in wireless networks indicates that spectrum does not behave like ordinary property and requires a different commons based allocation and coordination regime one that encourages cooperation among users in order to increase available capacity. No obvious regime exists today. However, the current Internet regime for wired communication was formed from 25 years of innovation in an open and experimental environment. The resulting regime differs significantly from the previous regime that grew under the control of the telecommunications provider. The author calls for the development of a cooperative wireless network regime by starting with an open and experimental regime that encourages cooperation much the same as the starting point for the current Internet regime for wired digital communications.

This paper is a summary of an Aspen Institute sponsored in-depth roundtable session, written from the perspective of one informed conference observer (Bollier). The participants are leading thinkers in the many complex areas this paper covers (economics, systems theory, human behavior, human futures, information technology evolution, etc) and are listed on page 57. A selection of their key insights shared in the paper are listed below:

A "push" economy is geared towards mass production, anticipating consumer demand, and routing resources to the right place at the right time, to create standardized and mass produced products. By contrast, a "pull" economy is based on open, flexible production platforms that are used to orchestrate a broad range of resources. Instead of producing standardized products, "pull" model companies are demand-driven, and assemble products in customized ways that serve specialized or local needs, usually using "rapid" or "on the fly" processes.

Several global corporations are moving towards "pull" methods, and away from "push" models; ie., Toyota, Dell, Cisco, Li & Fung. These companies employ different variations of Value Network models, that share information about overall network performance and best practices for serving specialized needs, among hundreds or even thousands of partner companies that make up the network. This creates an intra-network knowledge commons. Some companies also work closely with Open Source Software projects, thereby expanding their "pull" network, and expanding their knowledge commons into a broader Open Commons via Open Source Software project contributions. Thus, "pull" business models also tend to be Network Value-Increasing, and Commons-based business models as well.

"Pull" models can also be platforms for creating "increasing returns dynamics." This is due to "pull" models being based around loose and flexible networks that are already configured to scale as growth occurs. So, growth does not incur the huge overhead costs in administration that "push" models must contend with. Pull platform key characteristics include modular and loosely-coupled networks, open channels that better harness the passion and commitment of innovation communities. "Pull" platforms also will tend to influence public policy with regards to education and innovation, as more companies tend to gravitate towards the "pull" models.

The areas where "push" models tend to succeed in business are in areas where people do not know what they want, and prefer to shop from pre-made selections (Ikea, Home Depot). However, there are even "pull" models to found here, in the form of user-driven innovation, such as mountain biking, extreme skiing, hot rodding, etc. In these pro-amateur niches, customers don't necessarily know what they want, but do want to be a participant in the "pull" network that creates the product.

How do you tax a product that is made in 23 different countries? "Pull" models are going to change the way that governments create policy as more companies gravitate toward them. This will influence laws about intellectual property, education, taxation and more.

"Pull" economies are not just centered around finding creative ways to "outsource/offshore jobs" away from one place and to the places where "labor" is "cheaper". Successful "pull" models have encouraged and aided "insourcing", where more jobs are created, for instance in the United States by "foreign sources (a total of 7 million cited by this paper), than are out sourced (a total of 600,000+ cited by this paper). This is because pull models seek out, not just the "cheapest" labor, but the best ways to add value to the production networks. So, they can scale to many participants around the world, regardless of local labor costs, to find the best participants needed for specific specialized productions.

The social dynamics of "pull" models are highly centered around creating relationships of trust, sharing knowledge, and close cooperation among network participants. In "pull" models, non-market value creation (tacit knowledge, intangible value) is generally steered towards a commons-based model. A commons is used as a "collective governance regime for managing shared resources sustainably and equitably." Many of these commons are made possible by networked information technologies (the internet).

Bollier suggests that "if online commons are going to be useful to business, companies will need to do more work to develop protocols for identity and reputation management". This is because the use of the commons is based around trust. It also due to the need for ways to measure qualitative value in intangible assets beyond money, like knowledge, individual performance and value multiplication, and network wide performance/value multiplication.

Roundtable participants also noted that "pull" models will pose challenges to current education regimes that are centered around training people to participate in "push" economies. One of the participants mentions that " Computers, software tools, and Internet resources make possible some radically new styles of learning. By using pull-based systems, students can function much like businesses in the pull environment: They can access resources they don't control and put themselves into flows of activity, rather than just building inventories of static, objectified "knowledge."

Anticommons property is defined to be a class of property in analogy to the commons in classical economic literature to explain some of the failures and difficulties in the transition from communist to market economies. Multiple owners have privileges in a resource in a commons. The overuse of that resource has been described, notably by Hardin, as the tragedy of the commons. Heller defines an anticommons property as a scarce resource in which multiple owners have the right to individually exclude others from its use, and no one has an effective privilege of use. Stalemate results in the , the underuse of a property.

Heller examines a paradox in Moscow after the dissolution of the Soviet Union. Storefronts remained empty even though the economy was growing and there was demand for consumer goods. In contrast, street kiosks in front of them filled with goods and customers.

He maintains that the phenomenon is due to a tragedy of the anticommons, an underuse of scarce resources due to the allocation of multiple new owners with the rights to exclude others from its use.

He compares the distribution of rights in commercial property (previously owned by the state with overlapping bureaucratic stakes) with other types of properties (e.g., individual apartments, communal apartments, and street kiosks.) In the latter cases, sometimes legal but more often brutally questionable means of resolving rights disputes results in more widespread use of resources in the absence of appropriate legal recourse.

While Heller devotes most of his attention to the underuse of commercial property in Moscow and other cities in the former Soviet Union, the notion of the anticommons has implications in the distribution of environmental and intellectual property rights.

Anticommons property may emerge in developed markets wherever new property rights are being defined. This can occur when new technologies make possible uses of, for example, intellectual property and environmental rights, unanticipated by the previously existing legal mechanism.

Once anticommons property appears, it is difficult to remedy the situation either through markets or subsequent regulation. Rather, Heller argues that care must be taken to avoid the accidental creation of anticommons property when new property rights are being defined by conveying core bundles of rights rather than multiple rights of exclusion.

“Along every conceivable dimension — from the intimate to the institutional — digital media force both individuals and organizations to redefine what kind of relationships create value.” The result of this paradigm shift isn’t about data and information, it’s about the value and priority that people place on the quantity and quality of their relationships.

Significant advances in technology have always altered how we perceive ourselves and our relationships. The automobile had an impact beyond simply moving from point to point B, and TV had an impact beyond delivering images and sound. Both of those wrought real and profound cultural change. Whenever a new medium emerges we have to look beyond the simple mechanics of the medium to the impact the medium has on the community. What’s important to recognize is that these new digital technologies aren’t simply evolutions of preceding technologies, but that these new technologies are now networked with each other. These new networks between networks have resulted in new relationships between networks that, in turn, have created new kinds of relationships between people.

This new phase of networked technologies allows individuals and institutions alike to create new ways of interaction. Intimacy, anonymity, trust, openness, access, passion, negotiation, hierarchy, coordination and collaboration can all be mediated, monitored and managed via networks ostensibly designed to carry bits. The value challenge has shifted from gathering and disseminating information to packaging and bundling it in unexpected ways.

What people crave is the chance to communicate and relate to each other in new ways – not simply to have access to a vast feast of information. The new technologies are directly related to the essence of being human. They challenge and stretch the traditional meaning of concepts like relationship, community and interpersonal expression. People expect more from these new technologies than simple job improvement, they want it to improve their working relationships with their boss, their colleagues, their subordinates and their clients.

Ultimately what is critical to people is value, and it is people, not information, that create value. According to “Netizens” their increased sense of belonging, of being part of a larger community, greatly outweighs the benefits of having a mass of information available. Failing to understand the transformational affects of the digital technology on culture itself will result in missed opportunities.

The Institutional Analysis and Development (IAD) framework developed by the Ostroms and their colleagues at Indiana University provides a foundation for studying a multitude of theories, models, and predictions of public choice behaviors in different systems of governance and organization.

Frameworks define the action arena to which it would be applied; the resulting patterns of interactions and outcomes, and the means of evaluating those outcomes.

A framework is a general language about how varying rules, physical and material conditions, and attributes of a community affect the structure of action arenas, the incentives for actors, and resulting outcomes.

Action arenas include an action situation and the actors in that situation.

An action situation includes:

• Participants
• Positions
• Outcomes
• Action-outcome linkages
• Control that participants exercise
• Information
• Cost and benefits of outcomes

Actors (individual or corporate) involve:

• Resources brought to the situation
• Values assigned to states of the world
• Methods for dealing with knowledge and information
• Selection processes for courses of action

Analysts can make strong predictions in tightly constrained situations of complete information: overuse of resources in an open commons where the actors do not share access to collective choice arenas.

Results are not as clear in situations where actors are embedded in communities with norms of fairness and conservation as well as the ability to communicate with each other.

Evaluation criteria can include a range of values for categories such as the following:

• Economic efficiency
• Fiscal equity among actors
• Redistributional equity (e.g., policies to care for poorer individuals
• Accountability
• Conformance to a general morality
• Adaptability to change

The IAD framework has been applied to various domains to make predictions of resulting behaviors in field settings. Examples of successful application include:

• Police services
• Urban public services in general
• Common-pool resources: these were studied in laboratory as well as field settings. The IAD framework was used to create a theory of behavior. Communication of participants affects behavior: if no communication was permitted, the results approximated that of non-cooperative game theory. Communication led to different, more positive, results.
• The IAD framework was used to develop extensive databases coding common-pool resources and diverse property regimes.

Dan Bricklin examines ways to induce a pool of users to contribute to a commons without extra effort, using the architecture of the commons (as in Napster's default to sharing in the way download directories are available) and leveraging user's self-interest. The key to understanding the success of Napster and other file-sharing technologies resides not in their 'peer-to-peer' nature but in the fact that they provide users with access to a database of desirable things and enable people to create a public good in the process of seeking their own interests.

Bricklin identifies three ways to fill a database: organized manual, organized mechanical, and volunteer manual.

CDDB succeeded at motivating volunteer manual data entry because it leveraged the desire for users to have their data in the database so that CDDB-aware programs could access it, for example when a user would insert a CD into their computer.

Bricklin calls this "harnessing the power of individual selfishness."

Napster cleverly avoided manual data entry by automatically indexing anything in the user's 'Shared Music' directory. Thus "storing the copy in the shared music directory [was] a natural by-product of the user's work with the songs."

Sharing is the default. This results in users "adding to the value of the database without doing any extra work."