Most of the system dynamics studies that evaluate decision making in complex dynamic task focus on the evaluation of performance over repeated trials and on the effectiveness of different instructional strategies as far as performance is concerned. Especially when a strategy seems to yield promising results in terms of performance, it becomes essential to know whether improved performance is due to improved system understanding, i.e. to correct rules or due to other rea-sons such as trial and error. This paper contributes to the emerging literature in system dynamics about assessing system understanding. Based on the way experts make decisions we develop a step by step guide to evaluate how the understanding of the system develops in the course of subjects interacting with the system through a simulation model. We apply our guide to the rein-deer management task and analyze data from previous experiments with the task. This applica-tion provides important insights for the further development of the questionnaires that are ap-plied for assessing understanding.
Ongoing research collaboration between Tecnun, University of Agder, Gjøvik University College and mnemonic AS (a Managed Security Services provider), investigates how to improve the operation of information security incident reporting systems. A large part of the research effort is collaborative workshops and a significant issue is how to engage the participants in an objective discussion. We have successfully employed small System Dynamics computer simulation models for this purpose. These models leave out many details and make a number of assumptions that are often wrong. However, that is precisely why they work so well. When experts are confronted with a wrong model of a system they know very well, they seem to have an urge to immediately correct the modeler, thus initiating discussion. Used correctly, these small conceptual models can kick start a collaborative modeling workshop, engaging the participants and immediately extracting useful information. This paper presents one such model and our experiences with using it.
This paper examines the role of information security incident reporting systems in the wider context of an information security management system. This work is based on four group model building workshops with participants from mnemonic AS, a Norwegian Managed Security Services Provider. We found that incident reporting is a crucial component in creating information security awareness among information system users. Our research indicates that increasing incident reporting rates does not necessarily mean poor security, but rather that the organisation is becoming more security aware, and, arguably, less exposed to information security risks. However, in an organisation with poor awareness, it is possible that incident reporting rates and risk increases simultaneously. Analogous results are known about industrial safety reporting systems and risk of organisational accidents.
This paper aims to support small medium enterprises (SMEs) in business planning through the use of system dynamics models. In particular, it has been hypothesized that through the use of a step-by-step system dynamics model building process SMEsâ entrepreneurs can better understand the net of cause-and-effect relationships underlying company financial and non-financial results. Such an approach also enables decision makers to improve their understanding about the figures portrayed in a balance sheet. In order to reach such a goal, this study has been carried out through the use of a case-study. The small company investigated is a leather handcraft operating in Indonesia. The paper makes explicit main feedback mechanisms underlying company customer base dynamics adoption process, production and inventory management policies, human resource management practice and machineries production capacity acquisition policy.
This study investigates the cause of a nearly twenty-five year decline in the percentage of U.S. born undergraduates earning engineering degrees. This dramatic decline has occurred despite incredibly high pay and low unemployment among engineers. On the surface this situation appears to violate the laws of supply and demand. A system dynamics model was created to represent the institutional forces and feedback loops present in the real-world system. This model internally represents the economic forces governing the choice to pursue science, technology, engineering, and mathematics (STEM) education, distinguishing features of quantitative knowledge that constrain its transmission, and factors determining the quality of STEM education in our schools. It is shown that high industry pay for STEM workers and low pay for STEM teachers can cause long-term self perpetuating labor shortages. The fact that mathematics performance has strong dependencies on past-knowledge exacerbates the situation. Policy proposals are simulated to test their ability to positively influence the system. The model is shown to exhibit tipping point behavior. Small reforms will have negligible impact while significant reforms could make the system move into a fundamentally better pattern of behavior, but only after considerable delays.
The stock and flow management (SFM) problem is of high relevance for a broad range of decision makers in society, business and personal affairs. Although in some areas highly sophisticated models and control concepts have been developed, the phenomena of excess stock and shortages are omnipresent. One recent explanation for these observations is offered by a stream of research, which finds evidence for widespread and persistent deficits in stock-flow thinking (SFT) capabilities even among well-educated adults. Building on this explanation, an attempt is made to test the hypothesis, that the better people understand accumulation, the higher will be their performance in SFM tasks. The results of a small sample pilot study indicate that the hypothesis of a one-dimensional cause-and-effect relationship between SFT and SFM performance has to be rejected. Therefore, Ackermanâs PPIK theory is introduced and used to formulate an elaborate causal model, which could be tested in future research.
Understanding how interactions between apparently race-neutral institutions and policies can produce racial disparities is essential to a Civil Rights Movement in the United States in the 21st Century. Moving from a discourse that focuses on intent as the determining factor in whether racism exists to a discourse that focuses on the existence of racial disparities and the structures that reproduce them requires a new language and vocabulary. Conceptualizing and operationalizing effective interventions that will reduce these disparities requires a new methodology. System dynamics can play a key role in providing both a language and a methodology to better understand the continuing presence of racial disparities across nearly every indicator of wellbeing. Most attempts to reduce racial disparities have met with considerable policy resistance, and modeling work must focus on identifying key leverage points. In this mostly qualitative work, causal-loop diagrams are pulled from relevant research and key reference modes are examined for insights into the structures perpetuating racial hierarchy. A dynamic hypothesis is proposed that the stock of African-Americans living in areas of concentrated poverty is one of the key drivers of racial disparities. Suggestions and opportunities for further modeling and next steps are also outlined.
This paper reports on an experiment comparing the relative effectiveness of standard group facilitation techniques with system dynamics facilitation techniques in a real world stakeholder participation process. The experiment tested the hypothesis that the system dynamics approach would lead to: (1) better decisions; (2) greater participant focus on relevant materials; and (3) higher procedural satisfaction. The system dynamics approach yielded better decisions but lower procedural satisfaction among participants.