Components of a system

The two attributes of a system which are specified by nearly all models are a boundary and a function or purpose. These are the two things that primarily define a given system. Other components of a system, and the generic terms used to denote them, vary widely from model to model, depending on the theoretical standpoint of those who describe it and the purpose it is seen as serving. Thus, looking purely at innovation system models, Edquist (2005: 188) speaks of the components of a national system as organisations and institutions, linked by functions and activities; Lundvall (2007) writes in terms of firms interacting with one another and the knowledge infrastructure; Asheim and Gertler (2005: 300) describe them at the regional level as the economic (or production) structure and the institutional set- up; Malerba (2005: 385) lists the three “main dimensions” of a sectoral innovation system as knowledge and technical domain, actors and networks, and institutions; while Bergek, Jacobsson, Carlsson, Lindmarki and Rickne (2005: 3) use “structural components” (actors, networks and institutions) and “functions” (knowledge development, resource utilisation, market formation, search, legitimation, entrepreneurial experimentation and positive externalities). On a much more generic level, Ackoff (1971) builds a model around the concepts of state, environment, events, reactions, responses, acts, behaviour, goals, processes and objectives, and on these bases constructs a definition of organisations, the nearest things in his model to a concrete entity.

It will be seen that many of these different definitions are matters of degree of generality. Looking, for example, at economic actors, we can think of individual workers nested within work teams and functional components of organisations, which in turn form part of

organisations or firms, which collectively make up networks, supply chains, regional clusters, industries, sectors, the economy, etc. While it is often possible to identify meaningful categories at many levels on this scale, only some of them will be relevant to the working of a given system. This goes back to Ackoff’s point, quoted above, that a system has an infinite number of properties, but only some of them will be relevant to the description or functioning of any given system. The more limited and specific in its

purpose a given system is, the more likely the relevant model is to be built around tangible entities and specific processes and functions.

Generally speaking, the elements, components or dimensions can be subdivided into entities and relationships. Entities can be seen as the nodes in a network of relationships. At least where economic systems are concerned, they can be further divided into the broad categories of persons, organisations, resources or objects, and institutions. The last

mentioned are especially important in most economic system models.

“Institutions” is used here in the economist’s sense of “formal regulations, legislation and systems as well as informal social norms that regulate the behaviour of economic actors” (Gertler 2004: 7). Amable (2000: 648) quotes North (1990) to the effect that “[h]istory- dependent institutions influence individual behaviour by defining the incentive framework in which agents take decisions.” He then goes on to argue that “institutions matter because they partly and imperfectly solve problems of coordination among agents, help promote and overcome opportunistic behaviour, make agents internalise externalities, whether inter- temporal or inter-personal, reduce uncertainty, etc.” Put briefly, institutions work by creating common expectations across national cultures about how others will react to the individual’s actions. In the words of Hollingsworth, who equates pure institutions to social habits, these latter “are the results of earlier choices and are a means of avoiding endless deliberation… institutions provide cognitive frameworks for individuals, make their

environments predictable, provide the information for coping with complex problems and environments.” (2000: 602-3)

The word in this technical sense is abstract and does not apply to organisational entities such as firms or universities. Most institutional economists emphasise this distinction as fundamental to their models (Amable 2000: 653). However, real entities often embody institutions to the point where they are difficult to disentangle in practice. The courts, for example, collectively represent an important legal institution because they embody rules, processes and expectations that determine how the rule of law will be implemented in a given polity, but this institutional role exists independently of the location or remit of any given court, of the judges or magistrates who run it, or of the decisions it makes. Large non-market public enterprises, such as railways and telecommunications carriers, are not individually institutions in their own right, but their existence is (or was) an economic institution with particular importance for skill formation in certain areas. A trade union, taken individually, is an organisation and not an institution; however, trade unions

collectively represent an economic institution because they affect the way things are done, especially at the workplace level, and clear behavioural differences are evident between nations or sectors which have active trade unions and those which do not.

One significant characteristic of institutions in the economist’s sense is that they are subject to increasing returns to adoption – in effect, a kind of network externality – and hence to path-dependence and lock-in which limit their flexibility to change in response to changing circumstances. This means that they are historically rooted, relatively stable features of a nation’s economic culture that survive through business cycles, changes of government, changes in political and market fashion, and structural change, and regularly outlive the original organisations or pieces of legislation that embody them. Another important feature of institutions is their polyvalence (e.g. Hall and Thelen 2006). The same institutions that govern economic behaviour can also function as institutions of governance or social interaction. Indeed, they are one of the main channels by which a nation’s society, polity and economy are coordinated, and hence explain the influence of each of these systems on the others.

Relationships are the means, processes and patterns through which entities interact, and thus make up the dynamic of the system. They include observable processes, activities, actions and events as well as more abstract dependencies and influences. As with entities, the choice of relationships to include in a model is subjective and depends on the purpose of the analysis and the perspective of the builders and users of the model. As noted earlier, systems approaches are characterised by a focus on relationships as opposed to the

behaviour of entities in isolation. This implies that their choice is generally more critical than that of the nodal entities to the working and appropriateness of the model. Given this, the choice of significant entities is often more or less arbitrary, at least in the initial stages of constructing a model.

Like many of the other distinctions made in this chapter, this one is neither necessary (an objective attribute of things or events) nor always self-evident. Certain elements of a system often seem to lie right on the boundary between entities and relationships. Institutions are an obvious case in point: their role in a system derives not from their physical existence or that of the instruments or organisations that embody them, but from the way they condition or constrain interactions between other entities. A less obvious case is networks. A network is a way of describing a pattern of interactions between several

entities, but once established, networks can often be treated as physical or virtual entities in the same way as the firms that make them up. Even organisations, in a pure systems paradigm (e.g. Ackoff 1971: 669), are systems in their own right defined by their interactions, but most models treat them as entities with an existence distinct from their behaviour. This can be seen as a special kind of boundary problem: individual systems describable as a pattern of interactions often behave as if they were entities once they assume the role of subsystems making up a broader system.

This abstract and generic account has been necessary for an understanding of the

intellectual bedrock on which the specific model set out in this thesis is constructed. Like many such accounts, it may appear confusing, vague and counter-intuitive in places precisely because of its abstraction and lack of specificity. Many aspects of the systems paradigm that do not make immediate sense when set out at this level of generality should become much more self-evident when they are grounded in a specific system model and linked to familiar types of evidence.