The effects of two behavioral decision making biases are evaluated within the context of a system dynamics model of a market for a commodity, overconfidence and availability. Overconfidence is modeled as an increase in the percent of a traders capital they are willing to commit to any trade and is found to have the effect of increasing profits for traders with good information relative to traders with poor information, as well as increasing the volatility of the returns for traders with good information more than for traders with poor information. The Availability Bias is modeled as a overweighting of information easily available to a trader and is found to have the effect of increasing the returns of traders with good information easily available to them and decreasing the returns of traders with poor information easily available.
This research introduces a relatively new evolutionary algorithm in computer science; Grammatical Evolution (GE), to the field of supply chain dynamics and bullwhip mitigation. As a proof of concept several experiments are conducted to derive optimal ordering policies for agents in a multi-tier supply chain. These results are compared with existing research using Genetic Algorithms (GA) to derive optimal ordering policies using similar simulations. This paper shows that GE can consistently discover the optimal ordering policies similar to the GA approach, and that in several experiments GE outperforms GA.
Even though non-linearity is said to drive the behaviour of system dynamics models, modellers do not have access to techniques that show this happening. The tools at their disposal to present model structure are powerful, but, by nature, static. Formal model analysis methods has made significant progress in explaining how structure drives behaviour, but the connection to standard model conceptualisation techniques have generally not yet been made. This paper presents work that links the results of recent formal model analysis techniques to traditional conceptual diagramming techniques. A prototype visualisation tool is used to create dynamic causal diagrams that display the changing influences of the elements of model structure over a simulation run; it shows the waxing and waning of the influence of different sets of loops.
Abstract
The aim of this paper is to describe an innovative Logistic Game® developed by the authors. It creates a competition between different teams in terms of strategic decisions in logistic and production problems in a real production system. The game is innovative in three ways. The first is the type of game. It is a game representing a production and logistic system, with the dynamic problems of a real system where, with finite resources, decisions have a relevant impact on performance. The second is the application of a simulation package to create the real scenario in which the competition develops, with the possibility to consider all factors (WIP, down times, line balancing, skills of person, etc). The third is its possible applications, since the game can be used not only as an educative facility, but also as a tool to assess the management skills of a future/present manager to face real and dynamic logistic problems.
Nemak, a Mexican enterprise devoted to the production of engine cylinder heads and blocks a market leader on the industry, tries to identify critical external factors to gain competitive advantage as well as to understand their influence on its overall performance in order to face the challenges of the global economy.
This paper presents the use of Balanced Scorecard based on a System Dynamics model that intends to be a decision-making tool for the company. The model is able to generate behavior trends on several different scenarios.
This paper shows a course design and its knowledge transfer process when teaching the changing paradigm of systems thinking, systems dynamics and simulation, through e-learning. The course uses the methodology for changing the analytical approach to the Systems dynamics thinking paradigm -in three months-; and was designed under the thought on-line approach. Action research method is used to observe the course evolution and to evaluate: new knowledge, skills developed by students and students improvements on the changing paradigm. This is an on-going research; we present preliminary results about the achievements up-to-date. Even that ST, SD and simulation are difficult topics, they can be successfully taught on the right e-learning environment. We can state that, teaching this kind of topics can result in a good learning experience for students. These results can contribute to broadcast the e-learning experience to other related topics.
National development planning is a decision process at the central government level that defines the strategic plan for a countrys long-term development. The System Dynamics Group at the University of Bergen in collaboration with Millennium Institute and the University of Iowa is developing an interactive learning environment for national development planning. BLEND is the acronym for Bergen Learning Environment for National Development. BLEND is a networked computer learning environment that constitutes a microcosm for real planning settings where policy makers play roles in a simulated government. The simulation model underlying BLEND is based on Millennium Institutes Threshold 21 model (T21) which has so far been applied in over 20 countries. T21 is a rather large model with a high level of detail. There is, however, ample evidence that learning environments are more effective when the models are simplified. The purpose of this paper is therefore to identify the key learning goals that BLEND has to address. Based on these we develop a simplified version of T21 that exhibits a lower level of detail and eliminates non-fundamental structural components.
This paper describes how the Threshold21 Model developed for the Government of Mali has been used to support the preparation of the five-year strategic plan for the country. The model proven useful at different levels in the planning process: (1) it enabled testing the coherence of data collected; (2) provided insights into the future development of current issues and the emergence of new challenges in the Business-As-Usual scenario; (3) supported the discussion of alternative policies and development paths; and (4) provided a basis for monitoring and evaluation of implemented policies. This paper reports of the use of the model at levels (2) and (3), describing how it enabled an open discussion on the critical assumptions for economic growth to be used in the strategic plan, and on the delays involved in the countrys growth process. Results from the model have been eventually incorporated in the national strategic plan.
This paper offers a computational model of profit-driven communication, when information-processing capacity of recipients is limited. Even though the model was inspired by the present situation in the direct online marketing industry, it has a wide applicability. In the model, profit-seeking communication firms exploit freely-available attention of recipients, while recipients allocate their limited cognitive capacity between competing tasks. We run numerical experiments to test various technical, market and regulatory proposals that aim at improving the social outcome. The paper makes a theoretical contribution to the economic literature and it also elucidates the current public policy debate about direct online marketing industry.
The service industry has grown considerably in the last century and investments in operational improvements have increased. Operational investments decisions have a huge impact on the profitability of the organization not only at present but also in the future affecting the sustainability of the organization. The service-profit chain is a framework that brings together several components in the service delivery process. Evaluations of service operations based on the service-profit chain and others have taken a static approach without any consideration to the feedback structure. We develop a system dynamics model to evaluate the impact of number of courses offered on profitability of training services. This is accomplished by incorporating an optimization structure using the hill-climbing algorithm. The results from the simulation are then discussed along with validation of the model.