CES

Centre d'Économie de la Sorbonne
UMR 8174

When Elinor Ostrom Meets Herbert A. Simon:
The Sciences of the Artificial as a Methodological Guide
“To Deal with Complexity”

Massimo CERVESATO

2025.07
# When Elinor Ostrom Meets Herbert A. Simon: *The Sciences of the Artificial* as a Methodological Guide “To Deal with Complexity”

**Author:** CERVESATO Massimo, [massimo.cervesato@univ-paris1.fr](mailto:massimo.cervesato@univ-paris1.fr)

**Affiliation:** Université Paris I Panthéon-Sorbonne, Centre d'Economie de la Sorbonne

## Abstract

In this paper, we aim to shed new light on the methodology that Elinor Ostrom used to study real institutional situations by analyzing the specific theoretical influences that led her to mobilize the notion of complexity. We show the hitherto neglected decisive influence on her work of the “sciences of the artificial”, a term coined by the political scientist, economist and precursor of systems thinking, Herbert A. Simon. On several occasions, Ostrom described Simon's book *The Sciences of the Artificial* as the precursor of a new methodology upon which she relied to understand the most complex system of all: human society. We thus demonstrate that the systems-engineering approach, in particular as established by Simon, played a greater role in Ostrom's work than is usually assumed. This way, we expect to provide a more precise understanding of the notion of complexity she used and the methodological choices that resulted from it. In so doing, we also illustrate how an interdisciplinary approach based on the notion of complexity can concretely be used in institutional economics.

**Keywords:** Ostrom (Elinor); Complexity; Economic Methodology; Simon (Herbert A.); Systems Science; Institutional Analysis.

**JEL Classification:** B25; B31; B41; B52.

## Introduction

Elinor Ostrom is best known for her work on common-pool resources (CPR), in which she shows how certain groups of individuals exploiting these resources are best able to find efficient and sustainable solutions to the social dilemmas they face without any external intervention (Ostrom, 1990). This thesis is based on an empirical analysis of concrete CPR situations involving a large number of different entities—institutional, cultural and bio-physical—and interactions between these entities, as well as on the modeling of the process by which the users involved conceptualize their opportunities and strategies, leading them to manage or not these resources efficiently and sustainably. In other words, Ostrom's empirical analyses are founded on a methodological apparatus aimed at coping with complexity, a notion that has gradually taken hold in Elinor Ostrom's research program on the institutional analysis of social-ecological systems (Ostrom, 1999, 2005). It is, therefore, no coincidence that she decided to name her Nobel Prize lecture in 2009 “Beyond Markets and States: Polycentric
Governance of Complex Economic Systems”, and that she concluded by inviting social scientists “to be willing to deal with complexity instead of rejecting it” (Ostrom, 2010a: 665).

Many commentators have already highlighted Ostrom's use of the notion of complexity and the tools she developed to address issues associated with it (Aligica and Boettke, 2009; Frischmann, 2013; Lara, 2015). Nevertheless, not all of them detail exactly what the notion of complexity refers to, or, more importantly, analyze specifically the structuring use of this notion in Ostrom's work. It is true that Ostrom is partly responsible for this neglect as she sometimes used the notion loosely.<fnref n="1" /> This led Lewis (2017: 12) to argue that her use of the notion tended more to be “a device for differentiating the Ostroms’ preferred approach to social analysis from earlier approaches to the study of social phenomena in general and public administration in particular” than a well-articulated, rigorously-defined concept. In this article, we intend to shed new light on the methodology employed by Ostrom as well as on the notion of complexity in her work by studying more closely the specific theoretical influences that led her to mobilize this notion. To this end, we show the hitherto neglected decisive influence on her work of the “sciences of the artificial”, a term coined by the political scientist, economist and precursor of systems thinking, Herbert A. Simon.

The filiation between Ostrom and precursors of systems thinking has only just begun to be explored by commentators. For example, Lewis and Aligica (2024) have shown the crucial influence of Ross Ashby's work in cybernetics on Vincent and Elinor Ostrom's conceptualization of self-governance. They claim that the influence of cybernetics has, until now, been largely underexplored in Ostromian studies, and they attempt to remedy this by analyzing the connection between Ashby and the Ostroms. However, while Lewis and Aligica (2024: 4) rightly stress the importance for Ostrom's work of the new developments of the 1950s and 1960s in administrative science and systems theory—in particular Simon's famous book *The Sciences of the Artificial*—they do not go into further detail about it. Moreover, many commentators who trace Ostrom's inspirations in the study of public or common goods only briefly mention Simon, or focus solely on the notion of “bounded rationality” (Clark, 2019; Tarko, 2021; McGinnis, 2021). While some have seen the filiation between Ostrom and Simon on systems thinking (Peneranda, 2012; Wall, 2014), enriching our understanding of Ostrom's methodological approach to complexity, their analyses do not provide an overall view. Thus, one can go further by showing in a more general way that the systems-engineering approach, in particular as established by Simon, played a greater role than is usually assumed regarding the notion of complexity and the tools Ostrom used to deal with it. Although Simon and Ostrom had few direct exchanges during their lives<fnref n="2" />, Ostrom explicitly stated on numerous occasions the essential role played by Simon in her own work, emphasizing his contribution to

<footnote n="1">¹ In her 1999 article “Coping with Tragedies of the Commons”, one of the texts in which her understanding of complexity is most detailed, she advances a standard definition: “Complex adaptive systems are composed of a large number of active elements whose rich patterns of interaction produce emergent properties that are not easy to predict by analyzing the separate parts of them” (Ostrom, 1999: 520-521).</footnote>

<footnote n="2">² When there is an exchange, Simon sometimes shows great enmity towards Ostrom, associating her fully with the public choice research program (Simon, 1996).</footnote>
systems science (Ostrom, 2004). Indeed, she described *The Sciences of the Artificial* as the precursor of a new methodology that she drew on to understand the most complex system of all: human society (E. Ostrom and V. Ostrom, 2004). By offering a detailed analysis of the inspiration Ostrom drew from Simon's work in systems and administrative science, we thus expect to provide a more precise understanding of the notion of complexity she used and the methodological choices that resulted from it.<fnref n="3" /> And in so doing, we intend to illustrate how an interdisciplinary approach based on the notion of complexity can concretely be used in institutional economics.

Firstly we show that the notion of complexity is central in Ostrom's work, particularly
in the way it addresses her methodological approach to the study of institutional situations,
which need to be understood as complex adaptive systems (Section I). The following section
describes more specifically what this approach refers to for Ostrom and what it borrows from
Simon (Section 2). This methodological approach is characterized in particular by a number of
Simonian analytical tools on complexity. We will take a closer look at three of them: (a) the
systemic approach via the notion of “nearly decomposable system”; (b) the necessity for
considering the adaptive evolution of systems, which favors the diversity of possible solutions;
(c) the necessity for conducting empirical research (Section 3). Lastly, in light of the preceding
argument, it will be possible to resituate some of Ostrom’s methodological choices, particularly
the elaboration of the *Institutional Analysis and Development* (IAD) framework and the design
principles. This will enrich our understanding of what the Ostroms meant by “the sciences of
the artifactual” for the study of human institutions (E. Ostrom and V. Ostrom, 2004: 139),
and this in turn will allow us to reinterpret her use of Simon’s bounded rationality (Section 4).

1) The importance of complexity in Ostrom’s work

Complexity is one of the main notions structuring Ostrom's work. However, it is unique
in that, unlike others (such as self-governance, polycentric systems, bounded rationality, etc.), it
characterizes a methodological approach rather than a research object as such. Indeed, if we
assume institutional situations are ‘complex’ systems, then it follows that we need
methodological tools to deal with it. This is how Ostrom conceived the role of “complexity
sciences” in social sciences at the end of her life:

My take on complexity is that it is a key set of concepts which are essential for
understanding how the world works. There are many situations where simple models don't
work – when there are 10, 15, 20 variables. [...] Here, the ideas of complexity can lend a
hand by providing a means of analysis and understanding the reality of these action
situations. [...] how do you unpack systems without such analyses? (Ostrom in Ramalingam:
2012).

<footnote n="3">³ While we sometimes refer to Vincent Ostrom in the course of the argument, the emphasis will be on Elinor, who was more interested in applied work and created appropriate tools for the research programs she was pursuing, whether about the management of public goods and services in metropolitan areas or of the commons (Aligica and Boettke, 2009; Wall, 2014).</footnote>
Thus, the notion of complexity is important for Ostrom because it brings together a number of associated concepts and methods that help study real-life situations. Lewis (2017) indicates that Ostrom's notion of complexity includes a series of parameters that she endeavored to define and understand throughout her career. According to him, the complex system in Ostrom's work should be comprehended as: 1) a set of elements (human beings, natural resources, cultural communities, etc.) interacting according to a structure of rules; 2) which produces emergent and spontaneous properties that cannot be reduced to the properties of the parts on which they depend, and that are difficult to predict; 3) which is made up of a series of nested structures; 4) and which is adaptive to its environment.

Ostrom's recognition of complexity came gradually. The theme began to be explicitly recognized by her and her husband in the late 1980s, especially when they started studying the commons. In January 1986, at the Ten-Year Prospectus of the *Workshop in Political Theory and Policy Analysis* they created in Bloomington, they stressed the problem posed by the complexity that social scientists face: "From our cumulative experience of working with theory, collective choice, and empirical consequences, we have become increasingly aware that the phenomena being investigated involve extraordinary complexity requiring multiple levels of foci of inquiry" (E. Ostrom and V. Ostrom [1986] in Clark, 2019: 102). Then, from the 1990s onwards, Ostrom began to devote more and more of her writings to how her work makes it possible to analyze complex systems. For example, while the theme is only touched upon in her seminal 1990 book *Governing the Commons*, her 1995 essay "Designing Complexity to Govern Complexity" explicitly sets out how her approach and results from 1990, particularly the design principles, address it. She states:

> if complexity is the nature of the systems we have an interest in governing (regulating), it is essential to think seriously about the complexity in the governance systems that are proposed. Without a deep concern for creating complex, nested systems of governance, the very processes of trying to regulate behavior so as to preserve biodiversity will produce the tragic and unintended consequence of destroying the complexity we are trying to enhance (Ostrom, 1995: 34).<fnref n="4" />

From then on, the notion of complexity was to influence all the research fields in which Ostrom worked in later years.

For example, the IAD framework she elaborated is a direct response to the complexity of the biological, cultural and social processes that Ostrom observed in institutional situations. In her Nobel Prize lecture, Ostrom says it is the “complexity and diversity of the field settings” that she studied that led her, with the *Workshop*, to develop the IAD framework (Ostrom, 2010a: 645; see also Poteete, Janssen and Ostrom, 2010: 56). Instead of providing a ready-made theory or model to explain certain observed social phenomena, the IAD is more akin to a framework that indicates the “set of variables and the types of relationships among variables that need to be examined in conducting any theoretical or empirical study of a particular type of phenomenon” (Ostrom, 1990: 192). It allows the researcher to know how to focus on the sets

<footnote n="4">⁴ See Lewis and Aligica (2024), who show how Ostrom follows Ross Ashby on this specific point.</footnote>
of rules, the bio-physical environment and the norms that influence the institutional structures
in which individuals evolve and interact.<fnref n="5" /> The IAD is thus a “metatheoretical” framework that
guides social scientists in grasping the complexity of the social world by giving them “a
consistent, nested set of concepts that can be used in our analysis, research, and policy advice in
a cumulative manner.” (Ostrom, 2005: 256). In analyzing Ostrom’s use of complexity,
Frischmann (2013) aptly notes there are two levels to be distinguished: I) a “substantive
lesson” that asserts that reality is complex; 2) a “methodological lesson” that tells us the
importance of continually adapting our methods to deal with this complexity. This is precisely
what she tried to do with the elaboration of the IAD and then with its extension to social-
ecological systems (Ostrom, 2007; see Wall, 2014).

If the notion of complexity refers more to a global methodological approach than to a
research object as such, it remains to characterize in more detail the origins and attributes of the
tools and methods—such as the IAD—that Ostrom associated with it. This is precisely where
the contribution of Simon is decisive.

## 2) Ostrom’s Simonian sources of inspiration for the study of complex systems

Our thesis in this article is that Simon played a far more important role than is currently discussed in secondary literature on Ostrom. Indeed, most of the commentators who link the two social scientists do so via the notion of bounded rationality (Chanteau and Labrousse, 2013; Clark, 2019; Tarko, 2021; McGinnis, 2021). Of course, on several occasions, Ostrom explicitly asserts the decisive role Simon played regarding her commitment to bounded rationality (Ostrom, 2005, 2010a). In one of her final writings, she even declares:

> The philosophical foundation of my research program was well established by the early
> 1980s, even though I have ventured forth on a rich program of research focusing on how
> institutions affect incentives related to common-pool resources [...]. The most important
> theoretical foundation has continued to be the theory of polycentricity initially developed by
> V. Ostrom, Tiebout, and Warren (1961) and V. Ostrom (1999), as well as Herbert Simon's
> (1957, 1978) *theory of bounded rationality and his stress on the importance of field
> research*. (Ostrom, 2017: 407, our emphasis).

The reference to Simon's notion of bounded rationality is explicit here. And Ostrom goes
further, acknowledging that it is thanks to him that field research has taken on a prominent role
in her work.<fnref n="6" />

Nevertheless, it is in a short essay on the ten books that most influenced her that
Simon's role can be seen most clearly (Ostrom, 2004). Indeed, while it is not surprising that

<footnote n="5">⁵ See Ostrom (2011) for a detailed presentation of the IAD and its evolution over time. See also McGinnis (2011) who provides “a simple guide to [this] complex framework”.</footnote>

<footnote n="6">⁶ This aspect is even clearer when, in the same article, she quotes much of Simon's 1957 conclusion in which he gives his methodological recommendations for grounding administrative science on empirical foundations (Simon, 1957: 247 in Ostrom, 2017: 394-395).</footnote>
*The Sciences of the Artificial* (Simon, [1969] 1996) features in the ranking, it is more striking to see that no mention of bounded rationality is made when justifying this choice:

> Due to its strong focus on design and on using components to build up a well functioning complex adaptive system, for me it is his most cogent book and related to many of my interests. [...] Simon understood better than most political scientists the need to analyze complex systems in terms of their subsystems and their subsystem's subsystem. He understood the importance of examining components all the way down to very tiny components of a very large and complex system – the holons of complex systems. (Ostrom, 2004: 45).

As Ostrom explicitly states, it is Simon's reflections on systems science that seem to matter most for her work. It is also interesting to note that in the same list, Ostrom cites Mayr's book *The Growth of Biological Thought* (1982) to emphasize the systems approach to complexity developed there.<fnref n="7" /> However, the approach used by Mayr is partly influenced by Simon himself.<fnref n="8" /> Considering Simon's thinking on systems science and complexity, it thus appears that his influence on Ostrom's work is more substantial than the notion of bounded rationality alone would suggest.

Some commentators have begun to highlight the role of Simonian ideas on systems and complexity in Ostrom's work. Wall (2014) points out, for example, that Ostrom drew on Simon's concept of "nearly decomposable system" to extend the IAD to social-ecological systems. Peneranda (2012) writes that an engineering approach developed in Simon's work may have influenced Ostrom in elaborating the design principles. However, one feels that these insights focus primarily on explaining particular operational tools, giving only a fragmented and embryonic vision of what Ostrom borrows from Simon on systems and complex thinking. It perhaps explains why, while Ostrom (2005: 270) argues that her research on complex, adaptive systems is "strongly influenced by the work of Simon", Clark (2019: 103-104) states that, before Ostrom, "the groundswell of systems theory and complexity science had not yet occurred", and that her work in this field "proceeded without support or guidance from others who had come before" her. In contrast to this, we uphold that Simon's reflection on systems science and complexity profoundly structures her global methodology and the tools she uses to conduct her work. It even allows us to explain her use of Simon's bounded rationality in a consistent way, as we shall see in section 4.

Indeed, the "sciences of the artificial", as conceptualized by Simon, ground a large part of the method employed by Ostrom on social systems, understood as complex systems, as she explicitly acknowledges in an article in 2004 with Vincent:

> The quest for meaning in the constitution of order in human societies cannot rely on the methods of the natural sciences. Instead, we face the challenge of developing and working with what might be called "the sciences of the artifactual" that are broadly applicable to the

<footnote n="7">⁷ See Lewis (2021) for an analysis of Mayr's role in Ostrom's methodological individualism.</footnote>

<footnote n="8">⁸ Mayr (1982: 53) states: "Simon (1962) has defined complex systems as those in which 'the whole is more than the sum of the parts, not in an ultimate, metaphysical sense but in the important pragmatic sense that, given the properties of the parts and the laws of their interaction, it is not a trivial matter to infer the properties of the whole.'"</footnote>
cultural and social sciences and the humanities. Herbert Simon has addressed what we call *the sciences of the artifactual in The Sciences of the Artificial* ([1969] 1981). We prefer the term artifactual to artificial. He addresses the basic issues that need to be emphasized. (E. Ostrom and V. Ostrom, 2004: 139, our emphasis).

The sciences of the artificial were born from the realization that humans are now evolving in a world that is more “artificial” than natural, made up of a growing number of increasingly complex “artifacts”. These artifacts range from the material objects we create and use to immaterial goods (knowledge, computer data, etc.), to the various organizations we evolve in, with its associated flow of information. What fundamentally characterizes these artifacts for Simon is that they are “being molded, by goals or purposes, to the environment in which [they live]” (Simon, [1969] 1996: xi). This malleability of the goals pursued by humans with regard to the environment implies a certain “contingency” in artificial phenomena, unlike with natural phenomena: “The contingency of artificial phenomena has always created doubts as to whether they fall properly within the compass of science. [...] The genuine problem is to show how empirical propositions can be made at all about systems that, given different circumstances, might be quite other than they are” (ibid.). This, then, is what needs to be surpassed by the elaboration of a new science, as Avenier (2019: 47, our translation) describes: “The central project of the sciences of the artificial is, then, to provide an epistemic framework better suited than that of the natural sciences to represent and understand phenomena in which both human intentions and perceived natural regulations are embodied”.<fnref n="9" /> The sciences of the artificial are thus composed of several disciplines: systems science, which enables the rigorous study of complex formal systems; cybernetics, which is more concerned with communication between systems and/or sub-systems; design science, which provides systematic methods for system innovation; cognitive sciences, which study the processing of information by any system that allows it; etc. This new research program aims both to understand the functioning and evolution of different artifacts, and to have well-founded knowledge and methods for developing new artifacts with desired properties (Avenier, 2019: 47).

It is precisely this objective that Ostrom seeks to achieve in the study of the management of public and common goods, particularly from the 1980s onwards. This is why she asserts that the issues and foundations laid down by Simon in *The Sciences of the Artificial* are the same as her own (E. Ostrom and V. Ostrom, 2004). In one of her earliest studies on the institutional framework that would become the IAD, she states that “[n]o guidance or control is possible without an understanding of how complex systems work” (Ostrom, 1986b: 473). Thus, what she finds in the sciences of the artificial is a series of concepts and tools already at hand for the study of social systems understood as complex systems:

> A crucial challenge at the current stage of development is the need to move toward theories of collective action and common-pool resources that acknowledge complexity and multiple levels of analysis [...]. To accomplish this difficult task, we need to recognize the importance of developing ontological frameworks and diagnostic theories and using both in future

<footnote n="9">⁹ Simon's development of this new research program took place in the mid-20th century during a period marked by a scientific enthusiasm for the recognition of the complexity of natural, biological and social systems and the need for associated tools and methods. See Durand (2017) on this subject.</footnote>
research. Ontological frameworks and diagnostic theories are used in medicine, biology, and information sciences to enable scholars to identify relevant causal processes within complex, nested systems. [...] *Within the social sciences, Herbert Simon (1981: 196) introduced a similar concept that he called a hierarchic system*" (Poteete, Janssen and Ostrom, 2010: 358-359, our emphasis).<fnref n="10" />

It is striking to see that the figure of the systems engineer, linked to these sciences of the artificial, progressively takes on a central role in her work from the 2000s:

> The complexity we have found in regard to common-pool resources in the field is not in any way unique to natural resources. For far too long, social scientists have viewed the physics of static, simple systems as the model of science we should try to emulate. [...] The engineers responsible for the design of airplanes and bridges—and now computers—have long coped with complex dynamic systems. [...] Design engineers of complex systems long ago gave up hope of ever doing complete analyses of all combinations of subsystems under all combinations of external environmental conditions. (Ostrom, 2005: 242)<fnref n="11" />

So, just as the contingency of artificial phenomena was a preoccupation of Simon's, as we have seen, so it was for Ostrom, who ruled out the possibility, or even the desirability, of seeking to "produce universal laws of political process and outcomes that hold anywhere and at any time (similar to the laws of physics)" (Ostrom, 2006: 6). The work of the social scientist is more akin to that of a systems engineer: "when the outcome of a particular process is unexpected, important, or has serious consequences [...], our task is similar to that of engineers who are asked to determine the cause of a failure of some complex equipment such as an airplane, ferry boat, or rocket" (ibid.).

Simon's research program for the sciences of the artificial was thus a decisive inspiration for Ostrom, both conceptually and methodologically.<fnref n="12" /> To understand what Ostrom concretely drew from Simon's work, we will now examine in closer detail the tools he developed to respond to the challenge of complexity.

### 3) Simon's analytical tools for the study of complex systems

Ostrom appropriated several analytical tools developed by Simon to address the complexity encountered in systems for her study of social systems. In our view, there are three principal tools, which we will detail in turn in this section. In the next section, we will see how highlighting these three Simonian tools sheds new light on Ostrom's methodological approach.

Firstly, Simon insists that most complex systems, whether natural or artificial, are to be understood and analyzed as “hierarchic systems” or as “nearly decomposable systems” (Simon,

<footnote n="10">¹⁰ See Lewis (2021) on the “realist orientation” of the “ontological commitments” in Ostrom's work.</footnote>

<footnote n="11">¹¹ Ostrom was a member of the Science Board of the Santa Fe Institute for five years, a research institute founded in 1984 and renowned for its study of complex adaptive systems (Ramalingam, 2012).</footnote>

<footnote n="12">¹² Nevertheless, we do not intend to assert that Simon is the only author who influenced Ostrom on this subject. See, for example, Ashby's role in Ostrom's conceptualization of self-governance (Lewis and Aligica, 2024).</footnote>
[1969] 1996).<fnref n="13" /> Hierarchical systems refer to “all complex systems analyzable into successive sets of subsystems”. Nearly decomposable systems form a particular class of hierarchical systems (ibid.: 184). For Simon, hierarchic systems can be decomposed into “the interactions *among* subsystems, on the one hand, and the interactions *within* subsystems that is, among the parts of those subsystems on the other”, with nearly decomposable systems being those hierarchic systems in which “the interactions among the subsystems are weak but not negligible” (ibid.: 197, author’s emphasis).<fnref n="14" /> While nearly decomposable systems would constitute most complex systems, the usefulness of the proposed categorization actually goes beyond mere description. In the chapter “The Architecture of Complexity: Hierarchic Systems”, Simon states:

> The fact then that many complex systems have a nearly decomposable, hierarchic structure is a major facilitating factor enabling us to understand, describe, and even "see" such systems and their parts. Or perhaps the proposition should be put the other way round. If there are important systems in the world that are complex without being hierarchic, they may to a considerable extent escape our observation and understanding. Analysis of their behavior would involve such detailed knowledge and calculation of the interactions of their elementary parts that it would be beyond our capacities of memory or computation. (Simon, [1969] 1996: 207)

Thus, this categorization has mainly a heuristic value for any researcher wishing to facilitate their study of complex systems. In Simon's view, it is one of the only techniques that can be used to understand the functioning and evolution of complex systems in a way that is adapted to human capabilities and resources. Indeed, to analyze and design complex structures, “one powerful technique is to discover viable ways of decomposing it into semi-independent components corresponding to its many functional parts”, enabling each component to be thought of “with some degree of independence” from the others (Simon, [1969] 1996: 128). While this may seem abstract in relation to human situations, Simon points out that “[m]uch of classical organization theory in fact was concerned precisely with this issue” (ibid.).<fnref n="15" /> For Simon, “the construction of a nontrivial theory of complex systems” requires a “theory of hierarchy”, in particular one based on nearly decomposable systems, which “simplifies the description of a complex system” (ibid.: 216). As we shall see, Ostrom drew on this very conceptualization to found the IAD (Ostrom, 2005) and enrich it to take better account of the ecological aspect of social systems (Ostrom, 2007; Wall, 2014).

Secondly, Simon advocates an approach to the study of complex systems based more on the recognition of the variety of possible evolutions than on a principle of optimization leading to a single solution, particularly in economics. This thought is similar to his criticism of

<footnote n="13">¹³ We reiterate Simon's ([1969] 1996: 183-184) definition of a complex system: “Roughly, by a complex system I mean one made up of a large number of parts that have many interactions. [...] in such systems the whole is more than the sum of the parts in the weak but important pragmatic sense that, given the properties of the parts and the laws of their interaction, it is not a trivial matter to infer the properties of the whole.”</footnote>

<footnote n="14">¹⁴ The notion of decomposability began to become a well-established concept for characterizing complex systems and organizations during the 1960s. For example, Ashby (1962: 256) also notes the importance of this notion.</footnote>

<footnote n="15">¹⁵ Simon ([1969] 1996: 200) also cites the input-output matrix in economics as an example of such a decomposition.</footnote>
standard rational choice theory (Simon, 1955).<fnref n="16" /> Here, however, the argument has more to do with the methodology to be employed in studying economic complex systems. He states:

> from the fact that an economic system is evolving, one cannot conclude that it has reached or is likely to reach a position that bears any resemblance to the equilibria found in the theory of perfect competition. Each species in the ecosystem is adapting to an environment of other species evolving simultaneously with it. The evolution and future of such systems can only be understood from a knowledge of their histories. (Simon, [1969] 1996: 47)

His speech to the Richard T. Ely lecture at the *American Economic Association* in 1977 helps us understand the argument advanced here. Simon criticized the systematic, even excessive, use of marginalist calculus outside the “traditional domains of production and distribution” (Simon, 1978: 4).<fnref n="17" /> Instead, Simon promoted a functionalist analysis in the social sciences, which was concerned with the realization and maintenance of individual or social “goals” (Simon, 1978: 3).<fnref n="18" /> What Simon was really pointing out is that, by stepping outside the traditional domains of economics, “it is not clear that anything new is added” with marginalist calculation than with “cruder and simpler arguments” of functionalist analysis, “since the parameters imputed to the system are largely unmeasured and unmeasurable” (Simon, 1978: 6-8). Functionalist analysis, on the other hand, enables us to understand how a system can evolve to maintain itself (whether it reaches an equilibrium state or not). Indeed, to consider a solution as such in the functionalist framework proposed by Simon, it is sufficient that it satisfies the objectives specific to the system's survival: “all that can be concluded from a functional argument is that certain characteristics (the satisfaction of certain functional requirements in a particular way) are consistent with the survival and further development of the system, not that these same requirements could not be satisfied in some other way” (Simon, 1978: 4). This is all the truer when the system and its associated environment are complex, in which case “there is no assurance that the system's momentary position will lie anywhere near a point of equilibrium, whether local or global” (ibid.), with each element continually adapting to the other elements with which it shares a connection. This is why Simon states in *The Sciences of the Artificial* that “the evolution of firms and economies [...] is probably best understood through an examination of its history” (Simon, [1969] 1996: 48). We shall see that this evolutionary approach played an important role in the elaboration of the design principles for the study of the commons (Ostrom, 1990, 2005).

Thirdly, Simon continually advocates the need for empirical work through field surveys, experiments or simulations. On this account, in addition to his work on the sciences of the artificial, Simon (1957) is best known for his book *Administrative Behavior*, in which he delivers a major critique of the science of administration, and in particular the “administrative

<footnote n="16">¹⁶ See Mongin (1984) for a detailed analysis of Simon's work on rationality.</footnote>

<footnote n="17">¹⁷ Simon explicitly takes as an example the article by Stigler and Becker (1977) on the endogenization of preferences in the case of music.</footnote>

<footnote n="18">¹⁸ For a presentation of functionalist reasoning in economic and social sciences, see Mahner and Bunge (2001) and Kincaid (2007).</footnote>
principles” traditionally used to define the type of organization that works best.<fnref n="19" /> Simon
disapproves the aprioristic and hardly operational nature of these administrative principles, since
they are not derived from empirical analyses based on the “efficiency” criterion that
organizations actually aim at: “studies of administrative agencies have been carried out without
benefit of control or objective measurements of results, they have had to depend for their
recommendations and conclusions upon a priori reasoning proceeding from ‘principles of
administration’” (Simon, 1957: 43-44). He aims to give a stronger methodological foundation
for administrative science by promoting a more empirical research program: “What is needed is
empirical research and experimentation to determine the relative desirability of alternative
administrative arrangements”, knowing that the “methodological framework for this research is
already at hand in the principle of efficiency” (Simon, 1957: 42). This concern for empirical
research would structure his research throughout his career. Indeed, for Simon, conducting
empirical studies is one of the solutions to the methodological problems associated with the
study of complex systems, empirical tests being the only thing that could guarantee the validity
of a hypothesis in his eyes. This seems all the truer in the case of complex systems, which are
defined by the fact that it is very complicated to determine the properties structuring them
solely from the knowledge of their components (Simon, [1969] 1996: 184). This is why “the
genuine problem [of the sciences of the artificial] is to show how empirical propositions can be
made at all” (Simon, [1969] 1996: xi). Thus, Simon asserts the need to base the new research
program of the sciences of the artificial on empirical research. He himself applies this proposal
on numerous occasions (Newell, Shaw and Simon, 1957; Newell and Simon, 1976; Simon,
1995b) and is always careful to return to the empirical evaluation of hypotheses, especially
when they refer to complex situations (Simon, [1969] 1996: 23, 52, 121).<fnref n="20" /> The importance of
empirical research in the study of any system is precisely what would influence Ostrom to
conduct field investigations in metropolitan areas and later in CPR situations.

To sum up, three main analytical tools characterize Simon's approach to the study of complex systems, under the name of the sciences of the artificial: 1) the analysis of systems as nearly decomposable systems; 2) the importance of the historical adaptation of systems to their environment against the notion of optimality; 3) the need for empirical studies to guarantee the validity of any scientific proposal. We must now show how Ostrom appropriates these three tools in her own approach to the institutional analysis of social systems.

4) The “sciences of the artifactual” for the study of social systems

In order to study “the constitution of open, democratic, self-governing societies”, E.
Ostrom and V. Ostrom in 2004 (139) assert the need to reject “the methods of the natural

<footnote n="19">¹⁹ Simon focuses on the work of Gulick and Urwick (1937), and Urwick (1944).</footnote>

<footnote n="20">²⁰ It is also what motivates him to formulate his critique of standard rational choice theory: “Our procedure will be to introduce some modifications that appear (on the basis of casual empiricism) to correspond to observed behavior processes in humans” (Simon, 1955: 104). See also Simon ([1969] 1996: 28-30, 38-39).</footnote>
sciences” and develop “what might be called ‘the sciences of the artifactual’”, in reference to Simon's work. They choose to use the term “artifactual” instead of “artificial” because they intend to focus exclusively on human social systems, leaving aside the generalization sought by Simon to any complex system. We now present the tools and results in Ostrom's work that exemplify best how she appropriates the Simonian analytical tools we have presented. Lastly, we show how our argument allows us to reinterpret Ostrom’s use of Simon’s bounded rationality.

Firstly, the development of the IAD and its extension into a Social-Ecological System (SES) framework stems directly from Simon's conceptualization of complex systems as nearly decomposable systems. In her 2005 book, in which the IAD plays a central role, Ostrom seeks to provide solutions for social scientists who want to study the social world by acknowledging its complexity. They face “a major challenge in identifying the appropriate level of analysis relevant to addressing a particular puzzle and learning an appropriate language for understanding at least that focal level and one or two levels above and below that focal level” (Ostrom, 2005: 12). To respond to this challenge, as she points out in her Nobel Prize lecture, she drew her “inspiration from the work of Arthur Koestler (1973) and Simon ([1969] 1981, 1995a) who both challenged the assumption that human behavior and outcomes are entirely based on a small set of irreducible building blocks” (Ostrom, 2010a: 646). For her, social systems are best viewed as hierarchical systems and nearly decomposable systems, in which “it is somewhat arbitrary as to where we leave off the partitioning and what subsystems we take as elementary” (Simon, 1981: 196 cited in Poteete, Janssen and Ostrom, 2010: 359). This is why she intends to provide a tool capable “of ‘dissecting’ complex systems into composite holons that are then dissected further” (Ostrom, 2005: 11-12).<fnref n="21" /> This is precisely what the IAD enables, as Ostrom explicitly describes:

> Simon (2000: 753) describes the characteristics of nearly decomposable systems: “They are arranged in levels, the elements at each level being subdivisions of the elements at the level above” (see also Simon: 1995a). [...] In this overview, I cannot list all of the basic elements of political structures. Instead, I will provide a brief overview of the Institutional Analysis and Development (IAD) framework [...]. *It is a framework for analyzing nearly decomposable systems* ranging from families, to neighborhoods, to large communities, to governmental units at a local, regional, national, or international level” (Ostrom, 2006: 6-7, our emphasis).

The IAD is conceived as “a multi-tier conceptual map”, in which the analysis of each component can lead to the analysis of its sub-components, which in turn can be broken down in greater detail according to the needs expressed by the researcher (Ostrom, 2005: 14). Thus, in the IAD, each institutional situation is defined by an “action arena”, itself composed of two holons: the action situation and the participants. The action situation is then characterized by

<footnote n="21">²¹ A holon refers to what Koestler defines as “nested subassemblies of part-whole units in complex adaptive systems” (Koestler, 1973: 291 in Ostrom, 2005: 11), i.e. subparts of a complex system that themselves form complex systems as such, and so on.</footnote>
seven variables<fnref n="22" />, and the participants' behaviors are modeled through three main variables that must be adapted to each specific situation. However, it is also possible to consider three exogenous variables to the action arena affecting its structure: 1) the characteristics of the bio-physical world attached to the situation; 2) the structure of the community (with its norms, habits, cultures, etc.); 3) the rules used by participants in their relationships. Each of these exogenous variables is made up of a large number of variables. Rules being the central object of institutions (Ostrom, 1986a), Ostrom proposes seven fundamental classes of rules, echoing the seven variables structuring action situations. Nevertheless, it is still possible to go further by detailing the syntactic composition of rules, in particular to dissociate them from norms or collective strategies. Thus, Ostrom also proposes an institutional grammar, which she calls ADICO syntax<fnref n="23" />, to recognize these elements and their evolution in each institutional situation (Crawford and Ostrom, 2005: 139-140). Lastly, it is possible to step back and study the interactions between several action arenas "linked together either sequentially or simultaneously" (Ostrom, 2005: 15).<fnref n="24" /> As we can see, the IAD corresponds well to nested conceptual maps presented "at scales ranging from exceedingly fine-grained to extremely broad-grained" (Ostrom, 2005: 11). Similarly, when she seeks to take greater account of the institutional and ecological environment by developing the SES framework from the IAD, she points out that "SESs are partially decomposable systems" (Ostrom, 2007: 15182). Once more, the Simonian method is advocated: because "[s]cientific progress has been achieved in the past when scholars have recognized that complex systems are partially decomposable in their structure" (ibid.), it is necessary to continue developing other levels of the framework that will be added onto those of the existing IAD.

Secondly, the study of the commons proposed by Ostrom (1990), resulting in the eight design principles, is perfectly in line with the Simonian logic of considering the adaptive evolution of systems rather than their optimal solutions. While Ostrom (1990, 2005, 2007) calls for never relying on "universal solutions" or "panaceas", whatever the institutional situation under consideration, the elaboration of the design principles shows a way of getting around this problem. For her, a design principle refers to an "essential element or condition that helps to account for the success" of institutions managing a CPR, promoting a sustainable management of the CPR and the conformance of users to the institutional rules, generation after generation (Ostrom, 1990: 90).<fnref n="25" /> These principles are special because they do not indicate ready-made solutions, but instead correspond to what the rules of an institutional situation must respect to enable agents to find solutions adapted to their situation. As Peneranda (2012:

<footnote n="22">²² The seven variables are as follows: (1) participants (who may be either single individuals or corporate actors), (2) positions, (3) potential outcomes, (4) action-outcome linkages, (5) the control that participants exercise, (6) types of information generated, and (7) the costs and benefits assigned to actions and outcomes." (Ostrom, 2005: 12)</footnote>

<footnote n="23">²³ The ADICO syntax enables us to analyze each component of an institutional statement: A stands for "ATTRIBUTES"; D for "DEONTIC"; I for "A/M"; C for "CONDITIONS"; and O for "OR ELSE" (Crawford and Ostrom, 2005).</footnote>

<footnote n="24">²⁴ See McGinnis (2011) for an account of these "networks of adjacent action situations".</footnote>

<footnote n="25">²⁵ These are the eight design principles: 1) clearly defined boundaries; 2) congruence between appropriation and provision rules and local conditions; 3) collective-choice arrangements; 4) monitoring; 5) graduated sanctions; 6) conflict-resolution mechanisms; 7) minimal recognition of rights to organize; 8) nested enterprises. (Ostrom, 1990: 90). For a discussion and a study of the validity of these principles, see Cox et al. (2010).</footnote>
28, our translation) points out, these design principles find their foundation in an “engineering approach that consists in designing procedural rules” where “[i]t is not the decision that is optimized” but “the process of coordinating actors in decision-making that is strengthened”. As a result, several sets of rules, depending on the specific and historical situation of the problem under consideration, can fulfill the same goals, such as the survivance of the common-pool resource and agents' conformance to collective rules. In other words, we find here the notion of functional equivalence that Simon ([1969] 1996, 1978) defended concerning complex systems, as we saw above. For this reason, it is not surprising that Ostrom stated the following about the design principles in 2005:

> At a recent colloquium where the design principles were discussed, Mike McGinnis made an interesting observation drawing broadly on the work of Herbert Simon. He noted that Simon has repeatedly stressed the complexity of designing humanly engineered systems whether they be computers, road networks, or institutional arrangements. In *The Sciences of the Artificial* (1981), Simon specially argues that no humanly designed, complex system can be fully planned to achieve optimal performance. Rather, he stressed that all complex systems must be built up from simpler components. [...] My own conclusion related to the impossibility of doing a complete analysis of a complex, adaptive system is, of course, strongly influenced by the work of Simon, as well as our research on coupled social-ecological systems. So, one way of thinking about the practical implications of the design principles is as a beginning point for conducting a broad search for appropriate means of solving problems. (Ostrom, 2005: 270-271).

This is even clearer when she explicitly states that no notion of optimality is automatically attached to this gradual adaptation of rules since each institutional CPR situation is too complex ever to be sure of achieving any optimality. Ostrom emphasizes that it is the very notion of 'optimality' that poses a problem for CPR situations: "In fact, given the high levels of uncertainty involved and the difficulty of measuring the benefits and costs, it would be extremely difficult to obtain a meaningful measure of optimality" (Ostrom, 1990: 59-60). And she continues in the associated footnote: "I prefer to argue that optimality is not well defined in a changing environment, including the capacity to change the institutional rules themselves" (Ostrom, 1990: 224). This clearly echoes Simon's comments (1978: 4): "when the system is complex and its environment continuously changing (that is, in the conditions under which biological and social evolution actually take place), there is no assurance that the momentary position of the system will lie anywhere near a point of equilibrium, whether local or global".

Thirdly, while the importance of conducting empirical research in Ostrom's work is well established (Aligica and Boettke, 2011; Frischman, 2013; Herzberg, 2015), few have noted the role again played by Simon. As early as 1971, in an article co-authored with V. Ostrom, they claimed to promote a new approach to the study of public administration, based in part on the public choice research program, but also on Simon's observations and guidelines for administrative science (V. Ostrom and E. Ostrom, 1971).<fnref n="26" /> It is from this point onwards that Ostrom clearly expressed her mistrust of any solution presented as panacea, and asserted the

<footnote n="26">²⁶ See Aligica and Boettke (2009) or Aligica (2019) for a comparative analysis of the public choice research program and Ostrom's work in Bloomington.</footnote>
need always to rely on empirical studies, whether in developing an operational vocabulary,
establishing measurements or conducting experiments. This explains in particular the numerous
field surveys conducted during the 1970s in the case of metropolitan areas, as she explicitly
states (Ostrom, 2017: 407). It also makes clearer what she refers to in her 2004 article: "Simon
also urged scholars to add simulation techniques to their tool kits. He did this very self-
consciously. He felt that many of the overly simple mathematical models used in policy analyses
were dead wrong and led to incorrect decisions if not tragedies." (Ostrom, 2004: 45). Here, her
criticism of economic models on collective action problems, which she regards as mere
"metaphors" unrelated to actual CPR situations, echoes Simon's criticism of "traditional
administrative principles", which he regards as mere "proverbs" unrelated to actual
administrative organizations (Simon, 1957). Ostrom's insistence on field research, experiment
and simulation throughout her career thus borrows Simon's commitment to recognizing the
importance of addressing the complexity of the systems under study through empirical analysis.

Lastly, the influence of Simon's conception of complexity on Ostrom's work enables us
to understand better her view of rational choice theories, which is actually consistent with the
general methodological approach developed here. Indeed, from 1990 onwards, she began
explicitly to deplore the lack of theory capable of accounting for the empirical observation that
individuals succeed in organizing themselves to manage a CPR without any external
intervention: "We have not yet developed a *behavioral theory of collective action* based on
models of the individual consistent with empirical evidence about how individuals make
decisions in social-dilemma situations" (Ostrom, 1998: 1, author's emphasis; see also Ostrom,
1990: 25-26). Her central criticism is that standard rational choice theory is too simplistic to
understand the complex reality of collective action, being limited mainly to "open competitive
situations" (Janssen and Ostrom, 2006: 39; see also Ostrom, 2005: 100-101).<sup>27</sup> This is why
she states that the analyst "needs to substitute the assumption of bounded rationality—that
persons are 'intendedly' rational but only limitedly so—for the assumptions of perfect
information and utility maximization used in axiomatic choice theory" (Ostrom, 2010b: 18).
Some commentators duly underscore the role of complexity in this critique (Lara, 2015; Lewis
and Petersen, 2023) and others duly note that she appropriates Simon's notion of bounded
rationality (Chanteau and Labrousse, 2013; Tarko, 2021). However, none of them goes so far
as to explain Simon's influence on Ostrom's conception of rationality *through the emphasis on
complexity and the related general methodological approach*. Yet, once again, there is a striking
parallel on this point with Simon's declaring almost fifty years earlier that "the concept of
'economic man' [...] is in need of fairly drastic revision" demanding to be replaced by "a kind of
rational behavior that is compatible with" real human capacities (Simon, 1955: 99). It also
explains why, when criticizing previous research on collective action problems in her Nobel
Prize lecture, Ostrom states that "the *basic assumptions* that were made at that time [...] have
been challenged by scholars around the world, including the work of Herbert A. Simon (1955)

<footnote n="27"><sup>27</sup> See also Tarko (2021) for a formal analysis of Ostrom's conception of bounded rationality; and Lewis and Petersen (2023) for a characterization of Ostrom's view on rationality through Sen's analytical categories.</footnote>
and V. Ostrom (2008)” (Ostrom, 2010a: 642, our emphasis). This reflects the importance in
her work of Simon's emphasis on introducing greater complexity into economic modeling and
rational choice theories.<fnref n="28" /> In this way, Ostrom’s use of bounded rationality should be
interpreted through her appropriation of a more general methodological approach—Simon’s
sciences of the artificial—to confront both the complexity of human reasoning and institutional
choices on rules in particular settings (Ostrom, 1990, 1998, 2005).

Conclusion

This article has shown the hitherto neglected influence of the sciences of the artificial as conceptualized by Herbert A. Simon in the methodological approach employed by Elinor Ostrom to deal with the complexity of social systems. The analytical tools of the complex analysis developed by Simon—the nearly decomposable systems, the importance of adaptive evolution, and empirical research—were appropriated by Ostrom throughout her career to create new tools and concepts capable of tackling the complexity that social scientists face. It is particularly well illustrated by the elaboration of the IAD, the design principles, her constant criticism of any universal solution devised without any empirical consideration, and even her reappraisal of rational choice theories of collective action. Exploring this engineering approach within Ostrom's work, inspired by Simon or others such as Ashby, sheds new light on her methodology, illustrating how an interdisciplinary approach based on the notion of complexity can develop positively for institutional economics.

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