It is critical to investigate the development, diffusion and utilisation of emerging technologies in relation with each other, as well as with incumbent technologies. This is particularly imperative in sectors such as energy and transportation that struggle with both economic concerns (e.g., resource scarcity) and ‘grand challenges’, such as unsustainable consumption and production and greenhouse gas (GHG) emissions.
This thesis takes a biological perspective and investigates whether technologies in an industry interact with one another in the same way that populations do in an ecology. The biological inter-population relationships analogy is applied to the three powertrain technologies of internal combustion engine, hybrid and battery electric vehicles (ICEV, HEV, and BEV) in the United States (US) automotive industry. Inter-powertrain relationships are studied in the early technological lifecycle (TLC) stage, known as an ‘era of ferment’, as it is characterised by an increase in technological variations, intense competition, high market uncertainty, and the frequent exits and entries of firms.
This thesis conducts a qualitative and quantitative explanatory–exploratory study through a three-staged research design of narrative (conceptualisation), quantification and simulation. In the first stage, it conducts a qualitative explanatory–exploratory study to construct the conceptual framework. Adopting the technological innovation system (TIS) framework and the biological relationship modes, a dynamic approach to socio-technical interactions between technologies is proposed, called ‘dynapstic’. The various dimensions of the dynapstic framework are initially demonstrated by narrating some case studies, especially in the transportation and energy sectors. In the second stage, it conducts a quantitative explanatory–exploratory study to quantify the individual dimensions of the dynapstic framework. The biological Lotka-Volterra (L-V) equations are applied to quantify the individual socio-technical dimensions of powertrain technologies for the period 1985 to 2016. In the final stage, this thesis conducts a simulative explanatory–exploratory study to comprehensively simulate all the individual dimensions of the dynapstic framework. Feeding all the L-V quantifications and estimations from the second stage, all the individual socio-technical dimensions of powertrain technologies are integrated via an extensive system dynamics (SD) modelling for the time horizon of 1985 to 2050.
This thesis illustrates that the internal dynamics of one powertrain technology become coupled with the internal dynamics of another powertrain technology through what is referred to as ‘co-dynamics’ in the dynapstic framework. Some of the proposed co-dynamics are entrepreneurial spawning, policy transfer, knowledge recombination and resource redeployment. Co-dynamics are illustrated to carry a mix of positive, negative and neutral influences between powertrain technologies that shape the various biological relationship modes between them, such as competition symbiosis, commensalism, parasitism and amensalism. These co-dynamics eventually lead to the build-up of shared structural elements or ‘couplings’ between powertrain technologies, such as overlap actors, knowledge overlap, institutional overlap and resource overlap.
The findings throughout the three stages reveal that while inter-technology relationships can be multimodal and multidimensional, their nature and extent may undergo temporal transitions and suspensions over time. This thesis extends the TLC and strategic management literatures by challenging the assumptions for pure competition and for explicit dimensions, as technologies are illustrated to interact with each other in other forms (e.g., symbiosis, parasitism and commensalism) and for implicit dimensions (e.g., knowledge, policies, expectations and collaborations). It additionally contributes to the path dependency and sustainability transition literatures by revealing that transition processes are not only a result of path dependence, path creation and path destruction, but also a result of cross-path socio-technical interactions via positive and negative internalities and externalities. In particular, the TIS framework is made more outward oriented—first, by accommodating co-dynamics as a complementary dynamical unit of analysis to the conventional structural unit of analysis ‘couplings’, and second by proposing two new TIS motors, ‘motor of creative destruction’ and ‘motor of creative accumulation’. Finally, it contributes to the sustainability transition literature by challenging the transitionary, parasitic definition of hybrid technologies.
This thesis informs transition managers and policymakers that their policy mixes may possess a triple nature of ‘creation’, ‘destruction’ and ‘accumulation’. Because their policy mixes may not only generate positive or negative internalities for the intended technology, but may also bring about positive or negative externalities in the field of other technologies. Taking a biological perspective, six types of strategies are proposed: competition, symbiosis, parasitism, commensalism, amensalism and neutral strategies. Considering the temporal transitions and suspensions findings, public policy makers are recommended to create and alternate their strategies in accordance with the changing multimodal and multidimensional relationships, but maintain a balance between them by strategically and proactively reconfiguring, modifying, facilitating and coordinating them over time. While public policy makers should avoid devising policies that may eventually lead to the demise of both incumbent and emerging technologies, their pro-entrepreneurship public policies should be preceded by pro-incumbent public policies, for instance, through exit options or transition supports such as knowledge recombination, knowledge continuity mobilisation, resource redeployment, and entrepreneurial recycling. Such an understanding informs policy decisions of when, and to what extent, one should invest in emerging disruptive technologies, divest from the incumbent technology, or pursue an intermediate solution between the new and incumbent technologies, while avoiding any dead ends. (available at http://hdl.handle.net/1959.13/1423920)