Research outcomes
The main study hypothesis speculates that technology substitutions may follow one of two principal substitution modes, driven by performance expectations or relative scientific and technological development efforts, and that it will be possible to recognise these modes through the emergence of patterns in available technology datasets. In this regard this study adapts existing literature and technology forecasting techniques, coupled with statistical and functional data analysis of historical patent data, in order to structure:
- the conditions required for presumptive and reactive technological substitutions to arise
- the formulation of a functional linear regression model that indicates the likely mode of adoption from key technology development indicators
- a system dynamics simulation framework for assessing the impact of technological substitutions
Combined, these elements provide a means to predict market receptivity and support technology strategy and innovation management. Equally, this enables both quantitative (i.e. data-driven) measures of scientific development to be considered alongside more qualitative sociotechnical influences as part of wider technology development and market adoption processes. The capability to identify and test the sensitivity of the mode of substitution for a given technology will reduce uncertainty in decision-making processes by providing a clearer view of the risk of obsolescence of technology options and designs at the earliest conceptual stages. This in turn would enable a firm to identify the transition points where new products or upgrades should be phased in, based on the translation of expected performance characteristics into projected market share, with increased confidence. A more focused technology roadmap can then be implemented that offers a reduced time-to-market, whilst allowing product and service strategies to be developed that are more robust to rapidly shifting technological, market, and environmental conditions. This approach also enables a shift away from purely product-based development strategies, as being able to compare dissimilar technologies allows promising general-purpose technologies to be identified earlier on, which are ‘product-agnostic’ (e.g. technologies that are likely to be of value irrespective of which product they are applied to). To begin with however, the characteristics and modelling of substitutions in large technological systems are first considered in more detail in the next chapter.