Innovation and industry evolution
The stages in the life cycle of an industry typically start with first applications of a new invention by technology leaders, followed by development and refinement of products and services, before becoming a mature industry with well-understood products and practices. Mature industries are past the early growth phase, their culture of technology has stabilised and the shape of industrial structure and processes has emerged. In many cases these industries are oligopolistic, with a few specialised firms dominating market niches in the supply chain. Consolidation leads to concentration.
The new technology that starts a cycle of industry development can be a general purpose technology (GPT) that becomes the basis of a new system of industrial production. The key feature of a GPT is ‘pervasiveness’, how it is used by other sectors in the economy and leads to ‘complementary investments and technical change in the user sections’ (Helpman and Trajtenberg 1998: 86). The examples originally used by David (1990), and broadly followed since, were steam, electricity and information technology. Lipsey, Carlaw and Bekar (2005) include two organizational GPTs in their list of two dozen since 9000BCE: mass production and the factory system; and lean production and the Toyota system. It is widely believed AI is a new GPT.
Thinking about the construction industry and the production of the built environment as an evolving ‘system of production’ provides a new perspective on the context and direction of innovation and its evolution since the first industrial revolution. Hughes’ (1987) life cycle model had seven phases: invention, development, innovation, transfer, growth, competition, and consolidation. Within those seven phases of the life-cycle are two interior cycles that divide an industry’s evolution into two stages: Cycle 1 is invention, development, innovation, and transfer, Cycle 2 is growth, competition, and consolidation.
Cycle 2 focuses on innovation in production and organization, when mature technological systems emerge and construction materials like cement, concrete and glass, and components like building management systems, interior walls, plumbing fixtures, lifts and elevators have become oligopolistic industries in a mature supply chain. A mature industry produces a specific culture of technology, embodied in the firms and social institutions of the system of production, and creates the tendency for an industry to develop along defined technological trajectories unless or until deflected or disrupted by a powerful external force.
A diverse cluster of industries with deep layers of specialised firms in a dense network of producers, suppliers and materials is a ‘technological system’ (Hughes 1987: 47). Electricity grids and railways have networks, telecommunications and air traffic use interconnected nodes, postal systems use existing networks, some are geographically large, some are local, some are narrow, some broad.
Construction innovation has been narrowly focused because construction is a mature technological system, but this is changing. With a technological trajectory based on AI and associated emerging production technologies, the commercial contracting part of the industry will adopt these technologies as they become viable. The organization and structure of the industry will then change in response to changes in relative costs as the economies of scale of digitized production technologies are realized.
AI as a new GPT may be the start of a new life cycle in building and construction technology, and may be as disruptive as steam power was in the nineteenth century to the master builders and craftsmen of the day. The organization of construction is currently centred on project managers and incremental innovation, but a transformed industry would be focused on integrators who combine site preparation with production and assembly of digitally designed and fabricated components and modules.
David, P. A. 1990, The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox‟, American Economic Review, Vol. 80, pp. 355 - 361.
Helpman. E. and Trajtenberg, J. 1998. Diffusion of General Purpose Technologies, in Helpman, E. (ed.), General Purpose Technologies and Economic Growth, Cambridge: MIT Press. 85-119.
Hughes, T. P. 1987. The evolution of large technological systems, in The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology, W. E. Bijker, T. P. Hughes, and T. J. Pinch (eds.), Cambridge, Mass.: MIT Press.
Hughes, T. P. 1989. American Genesis: A Century of Invention and Technological Enthusiasm 1870-1970, Chicago: University of Chicago Press.
Lipsey, R. G., Carlaw, K. I. and Bekar, C. T. 2005. Economic Transformations: General Purpose Technologies and Long-term Economic Growth, Oxford: Oxford University Press.
