ABSTRACT
The idea that artefacts can be conceived as networks of interconnected elements is not new in the literature. Here we build upon recent research on so-called Complex Product Systems (CoPS) as defined by, among others, Miller et al. (1995) and Hobday (1998). CoPS have been defined as ‘high cost, engineeringintensive products, sub-systems, or constructs’ (Hobday 1998). They differ from simpler, mass produced products in terms of the dynamics of the innovation process, competitive strategies, managerial constraints and industrial co ordination. According to Hobday (1998), four characteristics set CoPS apart from mass-produced goods: (a) they are high-cost systems composed of many interacting and often customized elements; (b) they exhibit emerging properties; (c) their design, development, and production usually involve several firms; (d) the degree of user involvement is usually very high. First, CoPS are normally high value systems composed of many interacting and sometimes customised elements. Components are organized hierarchically. In addition, different components rely on knowledge bases that may exhibit dif ferent rates of change and technological opportunities (e.g. grinding operations versus catalysis). In particular, as different interacting component technologies are considered, the role played by uneven rates of change can be explored as a factor shaping the organization of innovative labour. Second, CoPS may exhibit emerging properties. For example, the scale-up process of a chemical route is not linear. This means that the basic chemistry of the process changes while moving from the laboratory bench up to full scale plant. Reactor behaviour can hardly be theoretically predicted, unless very stand ard processes are involved. Existing computer simulation tools can predict the behaviour of a whole process at steady state, but they can hardly help engineers figure out how the process will behave in dynamic situations, e.g. during the
start-up phase or during reactivation after a periodic shutdown. Therefore, CoPS exhibit a high degree of ‘systemic uncertainty’ (Bonaccorsi and Pammolli 1996). Systemic uncertainty is present when the interactions between different levels of the system are subjected to uncertainty. Third, in CoPS industries the degree of user involvement is usually very high. This is surely true of chemicals, where the operators are usually in charge of the conceptual design stage. Therefore, CoPS industries lend themselves to the analysis of the implications of changing patterns of division of labour between heterogeneous firms. Fourth, CoPS design, development and production usually involve several firms. Two points are worth stressing here. First, these networks of firms reflect the hierarchical nature of the product they have to deliver. Different firms will play different roles according to the breadth and depth of their tech nical and organizational capabilities. Second, as different agents are involved, ‘epistemic’ uncertainty is also present. Epistemic uncertainty derives from the need to co-ordinate the solution to a specific problem into a wide network of interdependent technological and managerial processes. For instance, Ancori et al. (2000) stress the problems related to developing ‘common languages, common classification and categorization’ systems when heterogeneous agents interact. While originally put forward to analyse the dynamics of capital goods indus tries (e.g. aero-engines, chemical plants, flight simulators etc.) the idea that any product can be analysed in terms of its constituents has received considerable attention in a variety of consumer industries. This is so for two related reasons. First, products in a variety of industries are embodying a widening range of functionalities. Second, such new functionalities build upon specialized bodies of knowledge. Within this stream of literature, increasing attention has been devoted to the analysis of a specific type of design strategy: modularity. The chief aim of modular design strategies is decomposing complex artefacts in simpler sub-systems which can evolve independently of each other. In a way, modularity is put forward as the solution to the increasing connectedness of technological and organizational systems.
