WP 2 NACHOS | Area: Establishment
Key research question of the sub-project:
What role does the decision-making behaviour of social systems play in the assessment and modelling of the uncertain investment and diffusion dynamics of innovations?
WP 2: Value-oriented steering of dynamic-adaptive technology diffusion, with particular emphasis on the social dimension of innovations
(PI: Prof. Dr Elmar Lukas | Co-PIs: Prof. Dr Michael Dick, Jun.-Prof. Dr Börner)
In addition to traditionally shorter product life cycles, exponentially rising costs for new product development and significantly increased international technological competition, technological, societal and political disruptions are making it increasingly difficult to assess the acceptance processes of innovations. Consequently, this gives rise to corresponding challenges and implications for the financial evaluation and management of corporate innovation projects, which lend particular significance to the threat facing technology conglomerates in particular – ‘Today a superstar, tomorrow a case for restructuring’, as the Handelsblatt aptly headlined in 2017.
To date, the financial literature has devoted only limited attention to these complex societal problems. When assessing the monetary benefits of innovations, such dynamics are primarily modelled using stochastic differential equations. However, as a result of this abstract, aggregated perspective, rule-based behavioural decisions made by innovation adopters, as well as interactions with groups and societies, are largely overlooked. In the social sciences and in physics – commonly referred to as sociophysics and econophysics respectively – such agent-based models have a long tradition when it comes to modelling dynamic, adaptive innovation systems. Macroscopic behaviours or trends are understood as the result of interactions between heterogeneous agents who interact with one another and/or with their environment on the basis of a set of rules. In the context of innovation, such models provide answers to questions such as: Under what socio-cultural or socio-economic conditions can innovations become established? What specific diffusion patterns can be identified? Feedback effects on, or implications for, entrepreneurial investment behaviour, on the other hand, are treated as secondary.
The aim of this research project is, on the one hand, to methodologically extend the theoretical strand of dynamic decision-making under uncertainty—which is rooted in neoclassical finance—to include agent-based models. Secondly, building on this, the project aims to investigate whether, and to what extent, selected societal factors—which are significant for both the genesis and the diffusion of innovations—influence firms’ investment behaviour in innovations or new technologies over time.