System Dynamics is no longer new, but its impact on the wider world is still quite immature. Newer technologies have been taken up much faster and more broadly, bringing about huge societal changes. Is System Dynamics fundamentally different, and do essential characteristics necessarily restrict it to narrower impacts and a slower rate of diffusion? The answers lie in innovation. This paper describes how innovation by practitioners will profoundly change the practice of System Dynamics and its societal impact.
This paper explores the dynamics of the development of grid-based electrification compared to off-grid electrification in Kenya. Consumers in Kenya who can afford to use electricity must choose to be connected to the national grid or to purchase a standalone system (usually diesel or photovoltaic generators). This decision is based not on price alone, but on the relative availability and reliability of the options. Although competition usually spurs growth, in this case it appears that the presence of strong off-grid choices may be hindering the development of the grid. If this is the true, energy planners might need to consider policy options which encourage the grid and off-grid markets to work as complements.
As we approach the 50th Anniversary of System Dynamics, researchers and practitioners have yet to reach a consensus on the components of systems thinking or a method for measuring systems thinking in individuals. This paper reviews the state of thinking about systems thinking and researcher reports of efforts to assess systems thinking. As the foundation for developing an assessment framework to be able to determine an individuals level of system thinking, we present a review of the literature and the results of a survey administered to participants at the 2006 Systems Thinking and Dynamic Modeling for K-12 Conference, in Marlboro, Massachusetts.
This paper builds a system dynamics model to study the impact of some activities of public corruption on economic growth. The model is articulated around a generic economy in which a public and a private sector take part. The sectors produce different goods using the same available economic resources. Both use labour and could employ different criteria for remunerating their workers. The difference between the private and public wage allows the model to justify the introduction and the persistence over time of public corrupt activities in the economy. The causal structure collects the decisions and the rules of behaviour of the economic agents. It reflects the normal economic activities and the interactions between them and the new causal relationships arising from the corruption activities. The feedback processes totally explains why corruption modifies both the public and private production as well as the wealth of some citizens. After formulating the decision rules of the economic agents, calibrating the values of the parameters and the initial conditions of the levels, a simulation exercise is carried out to characterize the growth attained by the economy under different scenarios taking into account different degrees of corruption and different ways for fighting against it.
The paper describes development of a continuous and discrete model of human resources transitions in a large organization. The model considers eight different ranks. The calibration of the model was performed where the historical data was used to determine time constants of transitions and fluctuations. Several simulation runs were performed in order to complete predictive validation of the model. Optimization of the model was performed in order to achieve desired structural dynamics. Pattern search algorithm was applied at this stage while considering the key parameters limitations. By performing the optimization appropriate strategy of the system structural development could be determined. Development and comparison of the continuous and discrete event model was performed. The discrete event model was applied in the validation phase. The hybrid approach to the problem provided higher level of confidence. System dynamics methodology proved to be appropriate as the tool for initial development of the model and structural validation reference.
Lake Superiors fishery resources have been subject to management control for more than a century. A goal of achieving stability of fish populations has been elusive. Present goals stated by management authorities have been expressed as hopes of achieving fish- community objectives, some of which may be impossibly exclusive in practice. A system dynamics model of major predator and prey fish populations of Western Lake Superior is discussed and demonstrated. Model simulations of fish population changes are compared to historical estimates. Model-implied results of alternative management policies are explored. Experiments applying past and alternative management policies indicate that a policy of reducing current high rates of predator stockings together with moderately increasing predator harvestings would contribute to long term population stability among both predator and prey fish populations of Lake Superior.
Strategic Human Resources Management (HRM) is a crucial factor of companies in which knowledge plays a vital role. But Germanys shrinking and aging population and their effects on the labor force potential within the next 10 to 15 years seem to be ignored by HR managers. Layoffs are still common practice and even early retirement schemes were common a short time ago. Supposably, managers do not have informative tools neither to evaluate ex ante specific HR strategies nor to forecast the development of stock and age structure of their workforce by simultaneously taking into account the intrasystem complexity and dynamic.
This case study in progress elaborates on the underestimated effects of employee fluctuation and different recruiting policies on the value of human capital in conjunction with a detailed aging chain. The author uses the feasible Transparent Human Capital Valuation approach to assess this human capital value and implements the approach as a co-flow within the system dynamics model.
The promotion of an applicable and holistic HRM tool is both a contemporary and overdue issue.
The purpose of this paper is to present a case study which illuminates the role of dy-namic models as enablers of better general management in the face of complexity. That role is usually accounted for either by the logic of the models or by the process of building them, namely in group model-building. Here, the relationship and interaction of the two, model logic with modeling process, is considered. We maintain that the conceptual understanding of managers is the crucial lever for better management. Our focus is on the role of models in improving such understanding. The empirical base and object of reflection is a large case study from an ultra-complex firm, where a model building and training venture was carried out. The main concern which aimed the project was to facilitate the ability of managers to cope with complexity and to enable effective organizational change. The venture enhanced both the systemic view and awareness among participants of the project, and therefore proved to be a good investment in management quality. In essence, it was an impor-tant move toward model-based management. A core group had been captivated by the power of systemic thinking in general and the use of models in particular. A seed had been sown.
System dynamics modelers face a broad spectrum of risks toward achieving project objectives. As they gain experience, their risk identification and management capabilities increase. By applying classification techniques from taxonomy development, the collective knowledge of previous modelers has been captured in a classification scheme for system dynamics modeling risks. The classification scheme allows modelers to more efficiently and effectively consider modeling risks by reducing the variation in their knowledge levels. The classification structure is focused on the steps of the system dynamics modeling methodology and the achievement of system knowledge and improvement objectives. As part of a broader modeling risk management approach, the risk classification scheme assists modelers in identifying and prioritizing the anticipated sources of modeling risks for a project. With that knowledge, they can more effectively identify the appropriate techniques for managing risks and then efficiently apply those techniques in a timely fashion through the entire project cycle.
Like other organizations, United States intercollegiate athletics departments face the challenge of operating efficiently and effectively. Performance measurement in this environment is made more challenging by the need to be successful both on and off the playing fields. With its focus on structural performance contributions, system dynamics modeling works well with data envelopment analysis, which is focused on input-output relationships, to provide a more complete understanding of performance measurement and assessment. This combined understanding supports policy analysis that contributes to performance improvement opportunities. This research outlines the success achieved by linking these two approaches, even with the system dynamics contribution limited to a qualitative model.