The dynamics of industrial emergence

The need to stimulate, identify and nurture new industries is a prominent challenge in advanced economies. While basic science represents a valuable source of new ideas and opportunities, it can often take decades before this science finally finds application in the market. While numerous studies have to date focused on aspects of industrial evolution, (e.g. innovation, internationalisation, new product introduction, technological lifecycles and emerging technologies), far fewer have focused on technology-based industrial emergence. It is clear that if assistance is to be provided to firms and industrial policymakers attempting to navigate industrial emergence then we need an improved understanding of the characteristics and dynamics of this phenomenon. Accordingly, this paper reviews published work from a range of disparate disciplines - evolutionary theory, social construction of technology (SCOT), complexity science, industrial dynamics and technology management - to identify these dynamics. Through this review we conceptualise industrial emergence as a co-evolutionary process in which nonlinear dynamics operate. Industrial emergence is sensitive to the initial availability of resources and the market applications, with growth dependent on the supply-demand coupling, agents' actions to reduce uncertainty and catalytic events. Through synthesizing these key dynamics we go on to propose a conceptual model for industrial emergence. © 2010 IEEE.

Exploring industry dynamics and interactions

Within strategic technology management and innovation, often stakeholders extrapolate past industry dynamics, trends and patterns into the future. One frequently used concept is that of 'lifecycles' - an analogy of a sequence of stages encountered by living organisms. Lifecycle terms - such as technology, product, industry - are frequently used interchangeably and without clear definition. Within the interdisciplinary context of technology management and forecasting, this juxtaposition of dynamics can create confusion rather than simplification. This paper explores some of the dynamics typically associated with technology-based industries, illustrated with data from the early US automotive industry. A wide range of dimensions are seen to have potential to influence the path of industry development, and technology roadmapping architecture is used to present a simplified visualisation of some of these. Stakeholders need to consider the units of analysis, causality and synchronicity of relevant different dynamics, rather than isolated lifecycles. Some graphical curves represent simple aggregation of components; other dynamics have significant impact, but incur time lags, rather than being superimposed. To optimise alignment of the important dimensions within any technology development, and for future strategy decisions, understanding these interactions is critical. © 2012 Elsevier Inc.