1. Two lessons from Ostrom's work on environmental commons

Elinor Ostrom's pioneering work challenged the notion that rational human beings would be helplessly trapped in social dilemmas. Much of her work focused on environmental commons and confronted the then-dominant and still powerful concept of the tragedy of the commons.

The term ‘commons’ generally conjures up the notion of a shared community resource, such as a public park or a common pasture. The term gained considerable notoriety among economists, political scientists, and other social scientists after the publication of Garrett Hardin's essay The Tragedy of the Commons in Science (Reference Gordon1968). Hardin (Reference Hardin1968) described the tragedy of the commons as follows:

1. (1) The positive component is a function of the increment of one animal. Since the herdsman receives all the proceeds from the sale of the additional animal, the positive utility is nearly +1.

2. (2) The negative component is a function of the additional overgrazing created by one more animal. Since, however, the effects of overgrazing are shared by all the herdsmen, the negative utility for any particular decision-making herdsman is only a fraction of −1.

Hardin's formulation has been the subject of extensive analysis and critique. At its core, the tragedy of the commons allegory illustrates a standard externality problem – each individual rationally maximizes his or her private welfare without accounting for external costs, i.e., the costs imposed on others.Footnote ³ Avoiding tragedy seems to require collective action to manage use of the shared resource. Simply put, unconstrained consumption is not sustainable, and thus, constraints must be introduced if the resource is to be sustained.

What should the constraints consist of? Hardin recognized two (top-down) solutions: government regulation and privatization. Government can constrain consumption by directly managing or regulating use of the shared resource. Alternatively, government can establish a system of private property rights delineating ownership of the resource. The former presumes that the government will take into account the aggregate effects and manage use of the resource efficiently over time, and the latter presumes that well-defined private property rights will facilitate market exchanges and lead to an efficient allocation of access and use rights, and consequently, efficient management of the resource over time (Demsetz, Reference Demsetz1967). Both approaches eliminate the commons; no longer do commoners freely choose for themselves how to manage a shared resource, for such freedom, Hardin claims, ‘brings ruin to all’. Both approaches rely on collective action through government to introduce constraints. The approaches differ substantially in terms of the manner in which ongoing (month-to-month, day-to-day, minute-to-minute) resource allocation decisions are made.

The tragedy of the commons allegory became the starting point for examining common pool resource problems and solutions. Many analysts assumed that the tragedy of the commons model described a normal problem (at least for common pool resources) and a binary solution set followed: to avoid tragedy, society must turn to government command-and-control (micro-management) or private property-enabled markets. Economists, political scientists, and many others analyzed and debated how well these two types of regulatory solutions work. Will command-and-control regulation by government lead to efficient outcomes or would society be better off relying on private ordering by markets?

Elinor Ostrom challenged the entire enterprise at its roots by asking two foundational sets of questions: first, how well does the tragedy of the commons allegory describe reality? Is it a useful theory for making predictions about real-world behavior of individuals sharing common pool resources? Does it describe a normal or exceptional situation? Does it provide a useful basis for choosing or designing regulatory solutions? Second, does the binary choice between government command-and-control regulation and private property-enabled markets reflect the full range of options? Are there alternative (bottom-up) institutions and/or means for collective action?

Critically, the two sets of questions are related, particularly when one begins with the tragedy of the commons allegory. Hardin blurred resource system with resource management. In his allegory, the shared resource system is the pasture, and open access sharing among herders is the resource management or governance regime. As did many social scientists, Hardin made a series of assumptions with respect to both resource and resource management that limit the generalizability of his allegory. As Ostrom (Reference Ostrom2007: 15183) explained:

1. (i) the resource system is a pasture;

2. (ii) no governance system is present related to the resource system;

3. (iii) the mobile individual resource units (the animals grazing on the pasture) can be identified and are the property of their owners and, when fattened, can be sold for cash;

4. (iv) a sufficient number of users, given the size of the pasture, are using the pasture to adversely affect its long-term productivity; and

5. (v) the resource users independently make decisions to maximize their own short-term returns.

Note that when the assumptions hold and fully describe the resource setting, the theory's predictions may be useful. But this is exceptional. Reality is considerably more complex. The tragedy of the commons allegory rarely describes shared resource settings in a sufficiently complete manner as to qualify as a useful theory for making predictions or prescribing regulatory solutions. More is needed.

Of course, it may be convenient to work within the confines of the allegory or model – and perhaps to assume that reality conforms to those confines – because doing so makes analysis tractable and leads to a well-defined problem and possible solutions to compare and evaluate. But this is a fundamental mistake and an example of distorting reductionism. It can lead the analyst to miss what is most important and focus on what is least relevant.

As Ostrom (Reference Ostrom2007) explained in the quote above, a slight change, which takes you outside the confines of the model, gives rise to solutions that completely escaped attention and would not be predicted to be relevant. Relaxing one of the assumptions, or just recognizing that some other factor is relevant to the situation, can change everything; cooperation to avoid tragedy becomes theoretically feasible without resort to one of the two ‘solutions’. As is now well understood in the field of institutional economics generally, community management, social norms, and other institutional arrangements are relevant solutions that can and often do outperform government regulation and market regulation.

Ostrom's contribution goes well beyond recognizing the limits of models and acknowledging what is theoretically feasible. While it is important to understand Ostrom's concerns about model-induced myopia, it is equally if not more important to appreciate how she responded to those concerns. In Governing the Commons: The Evolution of Institutions for Collective Action, for example, Ostrom (Reference Ostrom1990) explained how models such as the tragedy of the commons lead to myopic analysis of solutions and policy prescriptions. She suggested that neither the Leviathan (government regulation) nor Privatization (market regulation) is a panacea, and that model-induced myopia leads analysts to ignore alternative institutional arrangements that may be more effective tools for governance. But that is merely the beginning – literally, chapter one of the book (Ostrom, Reference Ostrom1990).

Ostrom was a scientist. Her response to concerns about model-induced myopia was to do the scientific work of systematically studying actual resource systems and governance institutions.

Over decades, Ostrom demonstrated through a rich empirical program how self-organized community governance often is an effective alternative for a wide range of shared resources. In some contexts, communities can and do solve tragedy of the commons, collective action, and other related resource management problems without (turning to) government regulation or market-driven allocation as a panacea. They do so in a variety of ways, often relying on informal mechanisms for coordinating behavior. Community solutions do not always succeed or always fail; they sometimes succeed and sometimes fail. ‘The temptation to seek out regulatory panaceas based on universal models, whether through private property, state action, or even notions of community, must be resisted in favor of a more nuanced approach’ (Madison et al., Reference Madison, Frischmann and Strandburg2010a: 676). Context matters.

Recognizing that people sometimes cooperate effectively and build institutions to enable sustainable shared use of common pool resources opened up the ‘solution space’ and focused scholarly attention on complexity, context, communities, and institutions. This broader field of vision not only brought informal institutions into view and encouraged their systematic study, but it also improved our understanding of formal institutions by revealing the many different ways that government, market, and community institutions depend on each other to be successful.Footnote ⁵ And it yielded two significant lessons, one substantive and one methodological.

Ostrom's Substantive Lesson:

Embrace complexity and context – or simply, reality. There is tremendous value in systematically studying actual contexts that present potential tragedies and institutional arrangements aimed at averting tragedies.

Be wary of model-induced myopia, supposed panaceas, and binary thinking. The deep problem with Hardin's tragedy of the commons allegory is not the allegory itself or its translation into a model or even a theory about how people might externalize costs in specific settings. The deep problem is the myopia that the model induced and the binary government-or-market thinking that followed. We consistently make the mistake of thinking in binary terms, individual or social, private or public, market or government. This leads to great distortions in our perceptions about the world and the plans we make. Reality is much more complicated.

Standing alone, this lesson may be underwhelming, or perhaps even offensive to the scholar. You might be thinking, ‘This is not a lesson. We all know that studying reality beats studying fictitious scenarios that do not match reality’. Naturally, the next question is how should one go about studying reality? This leads to the second lesson.Footnote ⁶

Ostrom's Methodological Lesson:

Embrace systematic, evolutionary learning through various interdisciplinary methodologies, theories, and empirical approaches, including case studies. There is tremendous value in a research framework that facilitates such learning while itself being subject to adaptation and refinement over time.

Ostrom did not presume community-based institutions were successful or ubiquitous. Community-based institutions required systematic study. To facilitate research on these institutions across diverse resource systems, Ostrom worked for decades on developing a scientific approach to studying and evaluating institutions. She devoted incredible energy to methodology, bridging disciplines, and enabling systematic, collaborative social science.

To systematize research, she developed the Institutional Analysis and Development (‘IAD’) framework.Footnote ⁷ It encourages interdisciplinary research and seeks to avoid path dependencies from disciplinary or methodological blinders, problems akin to the model-induced myopia discussed above. The IAD framework structures a common set of research questions to apply across diverse contexts. Ostrom (Reference Ostrom2005: 28–29) explained the relationships between a research framework, theories, and models:

The framework-driven approach is functionalist. It seeks to integrate theoretical and empirical research in coherent manner. Critically, Ostrom did not reject theories or models, but instead embraced the idea that different theories and models could work better for some observed phenomena than for others.Footnote ⁸ The IAD framework aims to systematize research efforts by facilitating ‘a more rigorous evaluation by matching and testing of theories and models with observed phenomena, and most generally, enable learning over time’ (Madison et al., Reference Madison, Frischmann and Strandburg2010a: 678). It depends heavily on empirical data, and consequently, on a systematic approach to gathering data.

The IAD framework identifies the most general set of variables that should be used to analyze all types of settings relevant for the framework and divides the investigation of such variables into groups.Footnote ⁹ The first group is exogenous variables and includes biophysical characteristics, community attributes, and ‘rules-in-use’ (or governance mechanisms). With respect to the analysis of a particular situation, these attributes of a commons are fixed. In the case of the lobster fishery, for example, these attributes might include the relevant biological characteristics of lobsters, such as the rates at which they age and reproduce; attributes of the community of fishermen, such as the proximity in which they live to others, the existence of familial relationships, and the skill sets needed for lobster fishing; and the rules – explicit or informal – that govern fishing.

The second group is the ‘action arena’, which ‘refers to the social space where participants with diverse preferences interact, exchange goods and services, solve problems, dominate one another, or fight (among the many things that individuals do in action arenas)’ (Ostrom, Reference Ostrom2005: 14). In other words, the ‘action arena’ is the context in which the exogenous variables combine in particular instances, leading over time to observed patterns of interactions and outcomes.

Ostrom's work emphasizes the diversity of possible combinations of exogenous variables that determine what actually happens in particular instances and, hence, the outcomes that result. The rules governing lobster fishing contribute to the activity's long-term sustainability, for example, but the patterns of interaction actually observed depend on the richness of the particular environment for lobsters, the degree to which rules are actually enforced, seasonal factors such as weather, and interaction with outside influences such as pollution and the state of the larger economy. Understanding the observed success or failure of a commons enterprise such as a lobster fishery may require accounting for all of these factors, even though it may turn out that outcomes are relatively impervious to some of them.

The foundation of the framework-driven analysis is structuring questions in clusters about the exogenous variables, the action arena, and the patterns of interactions and outcomes. This approach aims to systematize data gathering across complex, diverse phenomena while remaining amenable to diverse disciplinary perspectives and empirical methodologies.

One interesting aspect of the IAD framework is its accommodation of and heavy reliance on case studies. Case studies are an important component to the research program because case studies provide rich, detailed descriptions of institutional arrangements in context. In addition, case studies provide feedback for the research framework itself.Footnote ¹⁰ Of course, case studies also slow things down, making the empirical work more laborious, contentious, and incremental. Arguably, this is a virtue. Good (social) scientific research often takes time. A framework-driven approach is particularly attractive for studying the complex interactions between ecological and social (institutional) systems because of the many different disciplines and methodologies that must be brought to bear if progress is to be made (Ostrom, Reference Ostrom2009).

Ostrom's embrace of complexity goes further than studying reality and adopting a framework to accommodate different theories and methodologies. She also embraced collaboration among different people, disciplines, and cultures. She worked hard to ‘establish[] a common ground in the fractured academic world of the natural and social sciences’ (Becker and Ostrom, Reference Becker and Ostrom1995: 114). Her work was forcefully interdisciplinary, and throughout her career, she called on various disciplines to remove their disciplinary blinders. In her Presidential Address to the American Political Science Association, for example, Ostrom called for expansion of the ‘type of research methods regularly used in political science’ and suggested that more understanding is required across the social and biological sciences (Ostrom, Reference Ostrom1998).

Ostrom recognized that studying commons requires a kind of commons of its own, an interdisciplinary community for sharing skills, knowledge, research, and experience. So she built one.Footnote ¹¹ With ‘an ad hoc group of scholars including political scientists, anthropologists, economists, historians, and natural resource managers’ she founded the International Association for the Study of the Commons (IASC).Footnote ¹² She was the first President of the IASC. The IASC's three goals are

1. (1) To encourage exchange of knowledge among diverse disciplines, areas, and resource types;

2. (2) To foster mutual exchange of scholarship and practical experience; and

3. (3) To promote appropriate institutional design.

In pursuit of these goals, the IASC hosts major international conferences, publishes The Commons Digest and the International Journal of the Commons, and engages in many other activities that promote knowledge sharing and build social capital and connections among those concerned with commons.Footnote ¹³ Ostrom's legacy is most vividly seen in the thousands of people around the world, in many different disciplines and professional settings, who consider themselves a part of the research commons she helped construct.

2. Applying Ostrom's lessons to commons in the cultural environment (or knowledge commons)

Ostrom may be most well known among environmental scholars, but her lessons extend well beyond natural environmental resources. Here, I focus on commons in the cultural environment. This label sometimes confuses people; so let me briefly explain. I use the term ‘cultural environment’ to refer to the various cultural, intellectual, scientific, and social resources/systems that we inherit, use, experience, interact with, change, and pass on to future generations. Commons in the cultural environment thus refers to information commons, science commons, cultural commons, data commons, and other types of intellectual resource commons (Frischmann, Reference Frischmann2007; Frischmann, Reference Frischmann2012: 253–314; Madison et al., Reference Madison, Frischmann and Strandburg2010a). As shorthand, I and others sometimes refer to these as knowledge commons (Hess and Ostrom, Reference Hess and Ostrom2005). There are good reasons for casting a wide net and grouping information, science, knowledge, culture, data, and so on together. For brevity, I may refer to one member or another, but the analysis that follows applies to all.

It turns out that intellectual resources have their own ‘tragedy of the commons’-type allegory. It usually invokes the ‘free rider’ as the selfish actor. Replace Hardin's pasture with an intellectual resource – for example, an idea – and consider what happens when the resource is openly accessible to all. Everyone who can profitably make use of the idea will do so, as much and as often and in whatever manner suits them. ‘So what?’ you may ask, ‘Where is the tragedy in that? There is no depletion and so there is no ruin’. Ideas are public goods, not common pool resources; ideas are consumed non-rivalrously; they have infinite capacity and are not congested or depleted. Unconstrained consumption does not seem to pose a problem. However, there is a catch. We posited an existing idea. The trouble is that, unlike a pasture, ideas are products of human intellect; they must be created and often require investment. Unconstrained consumption of intellectual resources presents a risk for potential investors because it may be difficult to recover a sufficient return from those who consume the idea. We might call these consumers ‘free riders’ because they are getting a free ride on the idea creator's investment.Footnote ¹⁴ The result of free riding is not too much consumption; rather, it is consumption without payment, and that might lead to an underproduction of the shared resource, that is, the idea.

When viewed from a dynamic perspective, tragic underproduction of intellectual resources appears to be an inevitable social dilemma so long as consumption is unconstrained. In fact, the underlying problem can be modeled to look exactly like Hardin's tragedy of the commons allegory. At its core, the free-rider allegory also illustrates a standard externality problem – each individual rationally maximizes his or her private welfare without accounting for external costs. In this context, the social costs encompass the risk to investment and resulting underproduction of public goods over time. Again, the model can be easily translated into a classic collective action problem. Avoiding tragedy seems to require collective action to manage use of the shared resource. Simply put, unconstrained consumption appears unsustainable. A solution is needed.

In remarkable parallelism, many analysts simply assume that the free-rider allegory describes a normal (rather than exceptional) problem. Again, a binary solution set naturally follows. To avoid tragedy, society must turn to production subsidized by government or to intellectual property-enabled markets. Government subsidization does not involve introducing constraints on consumption. Instead, the underproduction problem is dealt with head-on. Government directs funds to research activities that yield intellectual resources and thus investment risks no longer matter. These intellectual resources can be shared openly and freely. On the other hand, intellectual property rights, such as patents and copyrights, lower the costs of exclusion, enable transactions, and mitigate the risk to investment posed by free riders. Intellectual property rights thus enable markets to function more effectively in supplying intellectual resources. Both approaches rely on collective action through government but differ substantially in terms of the manner in which resource allocation decisions are made.Footnote ¹⁵

The free-rider allegory, like the tragedy of the commons allegory, has played a powerful role in shaping the relevant discourse, policy, and law (Lemley, Reference Lemley2005). It figures prominently in the classroom (textbooks), courtroom (legal opinions), and halls of Congress (political debate).

Yet, we should focus on reality and be wary of powerful allegories. Following Ostrom, we should ask two foundational sets of questions. First, how well does the free-rider allegory describe reality? Is it a useful theory for making predictions about real-world behavior of individuals? Does it describe a normal or exceptional situation? Does it provide a useful basis for choosing or designing regulatory solutions? Second, does the binary choice between government subsidization and intellectual property-enabled markets reflect the full range of options? Are there alternative institutions and/or means for collective action?

Free riding – the act of freely using resources generated by another person without payment or even authorization – is normal. As I (Frischmann, Reference Frischmann2012: 161) argued recently:

The more difficult question is whether free riding that involves intellectual resources systematically reduces incentives to invest in such resources. Does such free riding normally lead to a social dilemma? The claim that it does hinges on certain premises about the behavior of investors. How does free riding impact actual people who invest time, money, effort, or other resources to produce intellectual resources? Does the risk of free riding diminish their incentives to invest?Footnote ¹⁶

Whether private incentives are in fact inefficiently suppressed by this risk depends on the type of investment, the intellectual resource in question, and the particular context. Many intellectual resources plainly are not subject to this particular concern, as evidenced by the fact that people consistently generate the resources without being disabled by concerns over misappropriation. In many situations, people make investments because the expected private benefits exceed their fixed costs, regardless of whether or not others free ride. Appropriating benefits through market exchange of the intellectual resource or some derivative product may not be relevant to the investor. For example, we engage in many intellectually productive activities because participation itself provides sufficient private benefits (Frey, Reference Frey2008: 35; Madison et al., Reference Madison, Frischmann and Strandburg2010a). Participation can be fun, intellectually stimulating, educational, service-oriented, among other things (Benkler, Reference Benkler2006; Schweik and English, Reference Schweik and English2012). Participation may not be effortless or free; it may require substantial investment. Regardless, the private value derived from participation may be sufficient, and external benefits conferred to others that use or consume the output (i.e., the intellectual resource) may be irrelevant to incentives to invest.Footnote ¹⁷ Similarly, in many situations, people create, invent, and innovate because the anticipated returns from their own use of the results are sufficient to justify the investment. There is a rich literature on user innovation that demonstrates how many significant innovations result from users seeking to solve their own particular problems, needs, or curiosities (Strandburg, Reference Strandburg2009: 871–888; Von Hippel, Reference Von Hippel2006). People often engage in such activities without disabling concern over free riding.

There are many other examples, but the point should be clear. Free riding does not necessarily reduce incentives to invest and does not inevitably lead to a social dilemma. Reality is considerably more complex than the free-rider allegory suggests, and there is no good reason for systematically marginalizing the many situations in which free riding that involves intellectual resources does not reduce incentives to invest. Such myopia is inexcusable. The bottom line is that the allegory rarely describes shared resource settings in a sufficiently complete manner to qualify as a useful theory for making predictions or prescribing solutions. Much more is needed.

My hypothesis is that free riding negatively impacts investment incentives and leads to social dilemmas in only exceptional circumstances, but frankly, I do not have empirical evidence to test this hypothesis (nor does anyone else, to my knowledge). My hypothesis is based on anecdote and observation, as well as a broad conception of the relevant universe of free riding phenomena and circumstances (investment opportunities). Regardless, as noted above, I confidently claim that free riding is ubiquitous and often quite beneficial in the sense that it is an important feature of competition and idea diffusion in society, often generating positive externalities as free riders use ideas productively (Frischmann, Reference Frischmann2012). Consequently, we must take care when prescribing solutions to solve supposed social dilemmas associated with free riding.

Even in situations where free riding reduces incentives to invest and a social ‘underproduction’ dilemma arises,Footnote ¹⁸ it turns out that there are many complications that are too easily overlooked. Ostrom's substantive lesson applies with equal force. First, there are no panaceas. Government subsidies and intellectual property rights are prominent means for addressing social dilemmas, but both ‘solutions’ are far from perfect; both are incomplete and introduce their own complications, biases, and inefficiencies.Footnote ¹⁹ Second, and more important for purposes of this article, there are many alternative solutions that people regularly employ to avoid tragedy. Commons in the cultural environment are an important set of alternatives that deserve systematic study (Hess and Ostrom, Reference Hess and Ostrom2005).

Before proceeding, it is important to be clear about what I mean when I refer to commons; the concept is remarkably fluid and varies considerably in its usage across different disciplines. Here is how I use it:

Commons is an institutionalized community practice, a form of community management or governance. It applies to resources, and it involves a group or community of people, but the commons itself is not the resources, the community, a place, or a thing. Commons is the institutional arrangement of these elements. ‘The basic characteristic that distinguishes commons from non-commons is institutionalized sharing of resources among members of a community’ (Madison et al., Reference Madison, Frischmann and Strandburg2010b: 841). Critically, there is incredible variance among commons in terms of the types of resources and communities, and consequently, in terms of the institutions through which governance is practiced or implemented. Of course, there are various obstacles to sustainable sharing. The tragedy of the commons allegory highlights one, and the free riding allegory highlights another. In reality, communities can and often do overcome these and other obstacles through constructed as well as emergent commons.Footnote ²⁰ And yet, as Ostrom made clear, commons can and often do fail, and thus demand systematic study.

Commons in the cultural environment refers to the institutionalized community practice of sharing information, science, knowledge, data, and other types of intellectual and cultural resources. Many communities regularly share such resources and overcome concerns about free riding and other dilemmas.Footnote ²¹

Most obvious may be research commons, given the importance of sharing and collaboration norms within scientific research communities (Merton, Reference Merton1979; Reichman and Uhlir, Reference Reichman and Uhlir2003). Reichman and Uhlir (Reference Reichman and Uhlir2003) examined scientific data commons, pressures on the ‘sharing ethos’ within various scientific communities, and institutional means for reconstructing commons. Cook-Deegan and Dedeurwaerdere (Reference Cook-Deegan and Dedeurwaerdere2006) examined research commons in the life sciences and mapped out some of the relationships between the structure and function of the resource commons and the relevant community. The National Research Council of the National Academies sponsored an international conference in 2009 that explored microbial research commons. Participants examined how upstream microbial research inputs – microbial data, literature, and research materials – can be managed as a commons (Reichman et al., forthcoming; Uhlir, Reference Uhlir2011).

Madison et al. (Reference Madison, Frischmann and Strandburg2010a) discussed the following less obvious examples: intellectual property pools, in which owners of patents in a technological domain license their patents to a common ‘pool’ from which producers of complex products can obtain all of the permissions needed to make and sell goods that use the patents; open source computer software projects, which offer users of open source programs the ability to create and share modifications to the programs;Footnote ²²Wikipedia, which offers users of this Internet encyclopedia the power to add to and edit its contents; the wire service for journalism operated by the Associated Press, which allows individual member media outlets the opportunity to publish work produced by other members; and ‘jamband’ fan communities, which record, share, and comment on musical performances of their favorite groups – with the permission of the artists themselves. We mentioned additional examples, including medieval guilds, ‘the modern research university and the departmental and disciplinary structures that lie within and above it’, and the Request for Comments (‘RFCs’) series that defines the technical protocols of the Internet. During a conference hosted at New York University in 2011, scholars presented case studies that ranged from rare disease research consortia to recreational roller derby leagues.

There are many different commons in the cultural environment. Yet we know very little about them: How do such commons work? Where do they come from, what contributes to their durability and effectiveness, and what undermines them?

In the past decade, scholars in various disciplines have become interested in studying these types of commons, and some have begun case studies. However, their research too often is focused narrowly on the specific case or an isolated area, such as academic publishing or open source software, and fails to investigate the broader institutional questions and to appreciate the need for systematic analysis.Footnote ²³ As a result, they tend to consider only a limited number of descriptive variables, which makes integration and learning from a body of case studies quite difficult.

Guided by Ostrom's methodological lesson and building on her IAD framework as well as her pioneering book with Charlotte Hess (Hess and Ostrom, Reference Hess and Ostrom2005), Madison et al. (Reference Madison, Frischmann and Strandburg2010a) developed a research framework to facilitate systematic study of commons in the cultural environment. The underlying nature and structure of the inquiry as well as the focus on complexity, context, communities, and institutions unites our project with her legacy. Nonetheless, we needed to adapt and extend the IAD framework to account for significant differences between commons in the natural environment and commons in the cultural environment. Most obvious, the resources are different, and as a result, the obstacles that must be overcome for institutionalized sharing to work are different. Thus, for example, the governance structures for commons in the cultural environment manage existing resources as well as production and integration of new resources. Another interesting complication is the complex role of legal institutions in delineating intellectual resources, for example, by defining what constitutes the expression in software that might be governed by open source software licenses. Notably, this complication raises resource boundary and corresponding resource management issues that are less salient for commons in the natural environment.

Madison et al. (Reference Madison, Frischmann and Strandburg2010a) explored these and other differences extensively, and explained why the differences call for a series of inquiries specifically tailored to commons in the cultural environment. It turns out that the exogenous variables are more intertwined in this context because separating the managed resources from the attributes and rules-in-use of the community that produces them can be incredibly difficult, if not impossible in some contexts. Moreover, distinguishing outcomes from resources and community attributes is not always strictly possible, since the interactions of the participants in these commons are inextricably linked with the form and content of the knowledge output, which in turn is itself a resource for future production. At this stage, we have identified the most general set of variables that should be used to analyze all types of settings relevant for our framework and divided the investigation of such variables into groups of questions, summarized in the following abbreviated outline:

1. (I) Background environment

   1. (a) What is the background context (legal, cultural, etc.) of this particular commons?

   2. (b) What is the ‘default’ status of the resources involved in the commons? Patented? Copyright? Open?

2. (II) Attributes of the commons

   1. (a) Resources

      1. (i) Identify all resources being pooled and how they are created or obtained

      2. (ii) Describe the characteristics of the resources, such as whether they are rival or non-rival, whether they are tangible or intangible, the technologies needed to create, obtain, or maintain them, and the technologies and skills required to use them

   2. (b) Community members

      1. (i) Identify community members and describe their roles

      2. (ii) Describe the degree and nature of openness of the community with respect to each type of community member and the general public

   3. (c) Goals and objectives of the commons

      1. (i) Identify the goals and objectives of the commons

      2. (ii) Identify the history and narrative of the commons

3. (III) Governance

   1. (a) What are the governance mechanisms of the commons (e.g., membership rules, resource contribution or extraction standards and requirements, conflict resolution mechanisms, sanctions for rule violation)

   2. (b) Who are the decision-makers and how are they selected?

   3. (c) What are the institutions that govern decision-making?

   4. (d) What informal norms govern the commons?

   5. (e) How do non-members interact with the commons? What institutions govern those interactions?

   6. (f) What legal structures (including intellectual property rules, subsidies, contract and licensing law, antitrust provisions) govern the functioning of the commons?

4. (IV) Patterns and outcomes

   1. (a) What benefits are delivered to members and to others (including innovations and creative output, production, sharing, and dissemination of those innovations and output to a broader audience, and social interactions that emerge from the commons?)

   2. (b) What costs and risks are associated with the commons, including, for example, any negative externalities?

Essentially, these clusters of issues guide more detailed inquiry. Case studies across disciplines and reviews of existing literature that address commons in the cultural environment will help specify relevant attributes within each cluster. We are developing a coding manual for case studies, and we expect the framework to evolve further as researchers apply it to specific case studies. This process is currently underway.

Taking another page from Ostrom's lesson book, we have begun to build an international and interdisciplinary research community. Many case studies are underway; more are being planned. It may be a while before we have any major scientific findings to report; it may be slow-going, laborious, and incremental. But that is fine because, as Ostrom showed us, good (social) scientific research often takes time.