Complexity and Local Interactions:
Towards a theory of industrial districts
David A. Lane
Università di Modena e Reggio Emilia
Acknowledgement: In preparing this paper, I profited from discussions with Robert Maxfield, Margherita Russo and David Stark, who kindly shared with me some of their knowledge about Silicon Valley, Sassuolo and Silicon Alley respectively. In addition, I learned much from my discussions over the years with my colleagues Andrea Ginzburg and Sebastiano Brusco about the ideas presented here and their relation with district phenomenology.
1. Introduction
In this paper, I sketch an approach to a theory of industrial districts from a complexity perspective. The theory would address three principal problems:
- How can we describe the organization of an industrial district?
- How can we characterize the kinds of production activities that we would expect to benefit from a district organization?
- What kinds of processes and structures might account for the persistence or failure of a district organization?
Proposed answers to all three of these questions are presented in the penultimate section of the paper. The concepts in which these answers are framed are developed in the first six sections, while the last section suggests what kinds of empirical and modeling methods might be applied to help inform, develop and evaluate the theory I am proposing here. In this introductory section, I provide a road-map for the rest of the paper.
What I mean by a complexity perspective is explained in section 2. I then turn to the task of defining a district and its organization. Since I want to define a district as a special kind of subsystem of what I call a market system, I have first to introduce this concept. That is the task of section 3, where I distinguish market systems from the more familiar notion of markets.
In section 4, I introduce two kinds of structures that together provide the organization of a market: networks and scaffolds. At the nodes of a network are agents – firms, project groups, individual human beings. The links between agents consist of processes of recurring interactions. Networks carry competences, through which the artifacts around which a market system is organized are produced and sold, new attributions for artifact functionality and new designs for artifact types and production processes are generated, and new markets developed. As new products come into being and new markets explored, the system’s network structure is transformed. The transformation processes are supported by various scaffolding structures, institutions that provide both a meta-stable identity for system agents and the possibility for renewal and change for the system itself. In my discussion of scaffolds, I will focus on two particularly important kinds: interaction loci and emergent rules and roles.
Now I can define an industrial district, as a geographically concentrated production subsystem of a market system, composed primarily of small and medium firms, with a decentralized, non-hierarchic organization. As a market system subsystem, a district’s organization can be described in terms of the competence networks of which it is comprised and the scaffolds through which these networks are formed and reconfigured, and the district identity is maintained and modified.
Two interesting questions need to be addressed about the particularity of districts in the class of all subsystems of market systems. The first has to do with the first defining characteristic of the district: its geographic concentration. Geographic concentration enables[1] local interactions among agents. I claim that local interactions are essential for agents to respond when the structure of their market system is undergoing a cascade of rapid changes, which affect both the artifact family around which the system is organized and the network of agents and agent relations that carries the system’s economic functionality. In section 5, I argue that effective action in situations of rapid transformation of the structure of agent and artifact space depends upon the generative potential of an agent’s relationships with the other agents with whom it interacts. As I argue in section 6, the generative potential of a relationship is determined by a set of characteristics that may be strongly affected by the locality of the participating agents’ interactions. Section 7 argues that districts are one solution to the problem of organizing effective local interactions in systems that “inherently” undergo cascades of rapid change.
The second question concerns an important feature of a number of geographical regions in which districts are located: the same geographical region contains more than one district, in the sense that there are clusters of firms based in the area that participate in different market systems. For example, both Silicon Valley and the Washington Beltway are the homes of both an information and communication technology cluster, as well as a biotechnology cluster, while the province of Modena has clusters in precision machinery, textiles and tiles, among other artifact families. How might we explain the existence of such “mega-districts”, or districts of districts?[2] As I show in section 7, the concept of scaffolding structures helps to answer this question: certain kinds of scaffolding structures provide support services to agents that participate in a district, independently of the market system in which the agent operates. Thus, these scaffolds can serve to promote the creation of new firm clusters that share the services they provide with existing clusters – and may even promote the integration of these clusters into pre-existing market systems, as new industrial districts.
Characterizing district organization in terms of competence networks and scaffolding structures may provide theoretical advantages, but it certainly introduces empirical difficulties. Consider for example one important implication of this idea: the firm is no longer a primary unit of analysis, but merely one type of node in the competence networks that carry out the district’s economic functionality. In the Carpi knitwear district, a man might be a worker one year, an entrepreneur the next, and a worker the following year, without changing in any substantial way his productive activities. A Silicon Valley entrepreneur might leave one company he founded, take off a year or two, then found another in a different market system – and immediately hire the same engineering team responsible for the success of his first company. Examples like thesehelp us to understand that an agent-network perspective is potentially much more powerful in describing how districts do what they do than a firm-based perspective. The difficulty is that most available data refer only to firms, and not to individuals, project groups, research collaborations, strategic alliances or other organizational forms that may be nodes in district competence networks. Moreover, the very definition I propose for network links has a temporal dimension, as it refers to “recurring patterns of interaction,” not static relations or one-shot events. What kinds of empirical research can shed light on competence networks and the processes whereby they form, carry functionality, and change structure? Similarly, how can scaffolding structures be identified and their functions observed? A related issue concerns the role of modeling in developing a complexity-based theory of districts and, in particular, examining district innovation processes. The concluding section of this paper briefly considers two emerging answers to these methodological problems: ethnographic methods and agent-based modeling.
2. Perspectives on complexity
The papers in this volume by Gell-Mann and Holland start from two different perspectives on complexity. Gell-Mann takes a theoretical perspective. The complexity of a system, he tells us, can be measured by the length of the minimal description of the system’s regularities. Thus, if we want to address the question of whether an industrial district is a complex system, we are forced to confront some hard ontological issues. How do we characterize a district in system terms – that is, what are its component entities, and through which kinds of processes do they interact with one another? Even harder: taking on the role of Gell-Mann’s judge, we need to decide what constitute a district’s regularities – and to frame a vocabulary in which we can describe them.
Holland’s approach to complexity begins phenomenologically rather than theoretically. For him, a complex system is one that behaves in a particular way. Roughly, the system is composed of a number of entities that have properties that in general differ from entity to entity; the entities interact with one another and the environment they inhabit; as a result of these interactions, their properties, the environment’s, and even their interaction modes may change. In the examples Holland presents, the entities’ structures – that is, the set of their properties – determine how they function – that is, the transformations they effect through their interactions with other entities.
A complex system, then, is a particular kind of dynamical process, determined by a succession of interactions among entities. The phenomena of interest in the dynamics of complex systems are often characterized as emergent: they refer to features that can be concisely described only by reference to a higher level of aggregation than the individual entities themselves and that persist for periods of time considerably longer than those in which individual entities’ interactions are denominated. Often, emergent structures self-organize, and this emergent organization of the system may constrain and channel the entities’ interaction patterns. To apply the phenomenological perspective on complexity to industrial districts, one must describe the district in terms of the agents that compose them and their modes of interaction, then search for “global” emergent structures and self-organization at the level of the district itself. We might even ask to what extent the district itself might be regarded as an emergent entity.
Both Holland and Gell-Mann emphasize an aspect of complex systems that could be described as cognitive. Holland refers to “adaptive agents” that adjust their actions on the basis of what they have learned from their previous history of interactions with their world; Gell-Mann calls the representation of the world on the basis of which such adjustments are made a “schema”, and prefers to reserve the term “complex system” itself for an entity with a schema, which can be thought of as its minimal description of the regularities in its world. This circle of ideas prompts a question rather novel to the district literature: are we justified in viewing the district itself as what Holland calls an adaptive agent and Gell-Mann a complex system? Or to put it another way: as we have already seen, a complexity perspective requires that we treat a district as a time-varying structure and that we try to understand how its structure determines its function; should we also view the district as a cognitive entity, and understand how its cognitive processes give rise to transformations in its structure?
Summarizing, the hallmarks of a complexity perspective include commitments to
- process and change, not stasis and equilibrium;
- a multilevel organization of entities;
- entity function determined by entity structure;
- distributed control and information-processing; and
- emergence and self-organization.
Whether it is useful to apply a complexity perspective to industrial districts depends on how rich an account of district phenomenology a theory founded on these commitments can produce.
3. Setting the context: markets and market systems
“The market” is an abstract entity defined formally by economists and employed informally by journalists, politicians and just about everyone else. It is a locus of impersonal exchange activities, where agents buy and sell products with defined characteristics, at prices that – according to standard economic theory – reflect supply-and-demand induced equilibria. Economic theory accords these prices the role of principal communication media between agents, who use the information prices convey to drive the actions they take in the economy. Relationships between agents do not count for much in “the market”. What matters is how each agent separately values each artifact in “the market”, values that “the market” then aggregates into prices for these artifacts. Frequently, in popular narratives about developments taking place in business and the economy, “the market” is assigned the central causal role.
By a market system, I mean a set of agents that engage with one another in recurring patterns of interaction, organized around an evolving family of artifacts. Through their interactions, the agents produce, buy and sell, deliver, install, commission, use and maintain artifacts in the family; generate new attributions about functionality for these artifacts; develop new artifacts to deliver the attributed functionality; and construct, augment and maintain new agents and patterns of agent interaction, to ensure that all these processes continue to be carried out, over time, even as the circumstances in which they take place are changing in response to perturbations from inside and outside the market system itself.
In a market system, the meaning of artifacts are up for negotiation. As a result of these negotiations, the artifacts take on value – not just in individual heads, but through a social process that takes place in concrete social settings. Agents learn more from each other than they do from prices, and they do not merely exchange information, they jointly develop interpretations. These interpretations drive action in new and hitherto unexplored directions.
Standard economic theory starts with the concept of “the market”. Of course, something like “the market” will play a role, often an essential one, in many of the interactions in which market system participants engage. However, in the most interesting district phenomenology, agent relationships often hold center stage, and many modalities of communication, from discourse based upon shared understandings through joint action coordinated by tacit knowledge, shape these relationships. Moreover, district functioning relies on non-market structures – like entrepreneur associations, user groups, trade fairs and standards organization – as well as shared attributions about agent roles and artifact functionality and rules that determine how agents may interact. These elements do not arise from market transactions, but from a complex network of agent interactions, whose description and analysis require a different set of ideas than standard economic theory has to offer.
4. Market system organization: networks and scaffolds
A market system can be viewed as a collection of transformation processes: for example, producing, selling, installing, maintaining, designing artifacts in the family around which the system is organized. In the course of carrying out these processes, other processes are enacted by agents in the system – gathering and interpreting information, setting standards, establishing new entities like strategic alliances or trade associations. All these processes are achieved through interactions among agents – individuals, working groups, divisions, firms, alliances. Since these interactions taken together deliver the functionality that permit the system to endure over time, they tend to be organized into recurring patterns, with each pattern identifiable by its set of participants, interaction modes, and frequency and duration of interactions. Each recurring pattern of interaction defines a network; each network may be said to carry a system competence; as they are enacted, these competences generate the transformation processes that deliver the system’s functionalities. Over time, of course, the transformation processes, the competences that enact them, and the networks that carry these competences change. But in the relatively short term, we may describe the system’s organization in agent space as the cross-cutting network of these competence networks.
If we view a market system from a somewhat longer time perspective, we notice that it is always undergoing perturbations, which may be generated from processes taking place within the system itself or may come from outside the system, as for example from large-scale macroeconomic shifts. In response, new networks are constructed and others change their structure, either by replacing or adding nodes or by altering the modes, duration or frequency of the linking interactions. Some of these changes may seem to happen “spontaneously,” but for most of them we can identify structures that have provided the opportunity and the means for them to happen. Thus, the fluid network organization of a market system is constructed, renewed, and extended by a longer-lasting set of structures that serves to keep the system functioning. We call these structures scaffolds, since they shape and support the competence network structure of the system as it undergoes construction and reconstruction.
Scaffolds come in two basic flavors – physical and cognitive. Examples of physical scaffolds include user groups and trade fairs, trade and professional organizations, and standards bodies, as well as communication media like trade and professional journals, company and organizational newsletters, and websites. Some of these scaffolds are generated inside the system itself, others come from elsewhere, for example from other market systems, from professions, or from government agencies. Interaction loci are a particularly important kind of physical scaffold. Their function is to provide a space within which particular types of interactions may take place.[3] All the examples listed above are or provide interaction loci. It is important to understand that all interactions are spatially located – and the way the space in which they happen is structured can have significant effects on the form the interactions take. Thus, interaction loci are crucial for constructing and maintaining agent relationships within a market system, and the kinds and organization of its interaction loci go a long way to determine the structure of the system’s agent-artifact space.