Stefan N. Grösser

We present a new strategy for the direct optimization of the values of policy functions. This approach is particularly well suited to model actors with a global perspective on the system and relies heavily on modern mathematical white-box optimization methods. We demonstrate our strategy on two classical models: market growth and World2. Each model is first transformed into an optimization problem by defining how the actor can influence the models’ dynamics and by choosing objective functions to measure improvements. To improve comparability between different runs, we also introduce a comparison measure for possible interventions. We solve the optimization problems, discuss the resulting policies and compare them to the existing results from the literature. In particular, we present a run of the World2 model which significantly improves the published “towards a global equilibrium” run with equal cost of intervention.

We explain that the extant framing of research relevance is skewed because it is centred upon irrelevance of much research knowledge to practitioners, while excluding or under emphasising the irrelevance of much practice knowledge to practitioners. Moreover, the current framing is skewed because the extant literature disregards the very common collaboration between researchers and practitioners. In addition, we explain that the current framing of research relevance is indistinct because theory, practice, and relevance are discussed in vague terms rather than specific terms. Furthermore, the current framing of research relevance is indistinct because there is little reference to theory knowledge. We argue that current skewed and indistinct framing obscures the complexity of relevance. As a result, overly simplistic assertions have been made about how relevance can be increased. We broaden and balance the framing of research relevance. We provide greater specificity in the explanation of factors that contribute to the complexity of relevance. We provide recommendations for addressing the complexity of relevance.

A business model is an essential part of a company - regardless of whether the company is a small entity or a global enterprise. Interest in business models in research and in practice has grown significantly in the last decade. Strategic initiatives and changes in business models are particularly cost intensive and uncertain. Thus, the analysis and understanding of a business model's structure and its changes induced by strategic initiatives is crucial. Approaches to business model analysis needs to support strategists and decision-makers, enabling them to evaluate strategic initiatives and alternatives in fluent environments where there is little or no prior experience. However, regrettably, the qualitative approaches currently available fall short of providing sound guidelines especially in uncertain, highly volatile situations that involve rapid technological developments and agile competitors, which middle managers and top-level executives are often face with. The quantitative approach used in the article concerning business model analysis is founded on a systemic simulation methodology which enables decision makers to obtain insightful experimental designs with a company's business model. Computational modeling helps to understand business models as complex systems with dynamic inter-dependencies and thereby it can complement existing tools. This article uses the approach for a case study in the e-commerce business. It discusses advantages and disadvantages of computational modeling as a strategy and management tool.

Current teaching and learning of system dynamics is based on materials derived from the expertise of masters. However, there is little explicit reference to the stages which beginners go through to become proficient nor what is learned at each of these stages. We argue that this hinders cumulative research and development in teaching and learning strategies. We engaged 15 acknowledged masters in the field to take part in a three-round Delphi study to develop an operational representation of the competence development stages and what is learned at each stage. The resulting system dynamics competence framework consists of a qualified, expert-evaluated, empirically based set of seven skills and 265 learning outcomes. The skills provide a common orientation, in the language of current educational research, to facilitate research, course design and certification efforts to ensure quality standards. To conclude this paper provides avenues for future work.

Purpose - The purpose of this paper is to inform information and communication design (ICD) for multi-national projects through the presentation of an example that does not rely on expensive expertise in graphic design. Design/Methodology/Approach - Action research involving participants from five different sectors. Findings - Successful ICD is not necessarily dependent upon costly graphic design of elaborate explanatory methods such as storyboards. Research implications/Limitations - The action research involved participants from only five different sectors. Practical implications - Economical ICD can facilitate development of understanding among multi-sector multi-national project participants. Originality/Value - The originality of this research note is that it addresses recent developments in ICD. The value of this research note is that an example is provided of application in a multi-sector multi-national project.