This thesis compiles three papers on different topics in computational economics: First, we present a new method to recursively integrate expectations over serially correlated latent variables with continuous support in maximum likelihood estimations, using highly efficient quadrature rules and interpolation; we apply the method to the dynamic discrete choice model of Rust (1987). Second, we present a method to use the constrained optimization approach to the estimation of dynamic models (MPEC; Su and Judd, 2012) in conjunction with grid adaption for state variables with continuous support; we use grid adaption by node movement, and derive sufficient optimality conditions for the underlying function approximation from the equioscillation theorem, which enables us to solve the estimation and the approximation problem simultaneously. Third, we present a simulation study using agent-based modelling to investigate whether a model of monopolistic competition can reach its equilibrium without common knowledge of aggregate demand and sophisticated utility optimization capabilities of the agents.
This paper examines the role of different material artefacts in the exploration of novel strategic topics. We conceptualize strategic topics as epistemic objects that become instantiated in multiple material artifacts, i.e., partial objects, which not only represent the epistemic object but also energize and direct the exploration process. Based on a longitudinal case study of a company that (in collaboration with other companies) explored the strategic topic of “flexible production”, we develop a new typology of material artefacts in terms of their relation to the strategic topic. We describe the layered nature of materiality, differentiating between different types of objectual and non-objectual material artefacts, and show how their interplay shapes the dynamics of the strategizing process. In particular, we explain how the constellation of material artefacts can lead to a shift of the strategic topic itself. We offer a conceptual model that captures the mechanisms in the dynamic interplay of different types of material artefacts and their effect on the process of exploration.
The increasing complexity of the modern world creates both higher risks and new interdependencies in the socioeconomic environment. To cope with these challenges powerful new tools must be applied to find sustainable solutions. System dynamics is a field that offers potential assistance in dealing with complex issues. However, managers and politicians often lack the knowledge and necessary skills to apply quantitative methods in their decision-making process. In contrast, qualitative approaches are easily understood and handled but have limited capacities for analysis. To address this gap, we have developed a bundle of tools tailored for managers and politicians facing complex problems. These tools enable executives to recognize effective levers and assess potential consequences of specific interventions in a highly interconnected system. The approach detailed here equips decision makers with a powerful method to develop, test, and communicate strategies to find long-term sustainable solutions for complex issues in business and society.
