IranKhodro Co. (IKCO) is the largest automaker in Middle East. Although this company has a particular interest in international markets, still domestic market is its main market. Because of government regulations, rivalry is not aggressive in domestic market, but real prices for various types of cars have depreciated in recent years. Another problem this company encounters is the instability of its market. Price fluctuations provide a good opportunity for speculators to benefit from buying automobiles in low prices and selling them high. On the other hand, the presence of speculators in the market aggravates the uncertainty because the manufacturer perceives a demand different from the demand of end users and this leads to an unbalanced demand-supply in market. In this paper we will discuss how sales policies of this company lead to above trends in prices and exacerbates its financial problems. Using system dynamics modeling, we are going to answer questions like: What has been the effect of different sales methods on price fluctuations? And what is the effect of different sales methods in long term?
System Dynamics has already proved useful in modeling various social phenomena and processes. As perfect examples of such processes, we can mention elections which are effected by many different social, economic, and political factors in every country. Often those factors are so interrelated and the pre-elections situations are so complicated that even the best political analysts not only cannot predict which party would win the competition, but also, after the elections, are unable to fully explain what factors contributed the most to one partys success in the elections. In this paper, we turn our attention to Irans presidential elections held in 1997 whose outcome was unpredictable even a few weeks before the elections day. Few people could believe the result of the elections, yet many politicians, analysts, economists, and sociologists tried to describe the sequence of occurrences that led to such a huge win for the Reformists party. Among all the explanations proposed by different people, we focus on a sociological analysis which considers various important factors in Iranian society. The high compatibility of the results of our models simulation with what happened in reality shows the great help that modeling can provide us in understanding social happenings.
The adoption of Electronic Health Records (EHRs) moves slowly despite a near consensus in the healthcare industry that their use could be a critical factor in addressing quality and cost issues. Barriers and benefits of EHRs, the adoption process, and potential remedies to speed up the process are subject to numerous studies. In this study, a casual loop diagram of the EHR adoption process is developed and discussed. Through this model, factors influencing the process and the relationships between them are examined. The model is intended to be the backbone of future stock-flow models which will provide a test bed to explore an understanding of the EHR adoption process and to evaluate various policy options.
The aim of this paper is to illustrate how System Dynamics can beneficiate small and medium international nongovernmental organisations (hereafter NGOs). As the majority of small NGOs are based on voluntary work, few adopt strategic and professional management to enhance and guarantee their sustainability. Such context rises several challenges which NGOs must learn to recognise and to face. A System Dynamics model will be presented and used as a decision-making-tool to help these organisations understanding part of the complexity surrounding them as well as some long term consequences of their actions. A case study will be presented.
This study uses parametric search to meet multiple goals in the behavior of dynamic systems. Parameters are searched using genetic algorithm. Main aim of this study is to discuss how multi-objective parameter search gives essential information about the system. A nonlinear electric circuit is one of the two dynamic models in this paper used for parameter optimization. The electric circuit model shows oscillatory behavior. A fitness function which evaluates period and amplitude and compares it with the desired oscillatory pattern is proposed. It is shown that time horizon for simulation based optimization can be crucial. The second model is a generic System Dynamics model, the stock management problem with second order supply line. The policy parameters are weight of stock adjustment and supply line adjustment. A fitness function that evaluates the settling time, overshoot, and steady state error is proposed. The search results provide some insight on both the fitness function and the system. The obtained results are satisfactory and they show that the response time of the system can be decreased by small overshoot. The paper is a step towards simulation based parameter search becoming an essential support toolbox for model building and policy design in System Dynamics.
System Dynamics methodology aims to model real complex dynamic systems for understanding them and coming up with policies to change the problematic dynamic behavior. In most of the dynamic systems of interest, humans play an important role. Hence, human behavior modeling is one of the goals of System Dynamics. This paper proposes Fuzzy Logic as a new tool to model human behavior. The paper uses the existing data from an experimental study on Stock Management Model and comes up with Fuzzy Logic players to mimic the behaviors of three different types of players. We believe that Fuzzy Logic will be useful in modeling decision making behavior as it also gives an understanding of why humans decide as they do which is in consensus with System Dynamics modeling.
This paper presents clear evidence of the value of group model building for supporting group decision processes. It responds to Rouwette et al.s (2002) challenge to take GMB assessments beyond unstructured single case descriptions that cannot be easily compared. This paper compares two parallel, real-world problem solving teams examining urban growth issues in Las Vegas, Nevada over the same two-year time period. One followed a system dynamics group model building process. The other used a more traditional group facilitation process. Data about the dynamics of discussions and the outcomes were collected from meeting transcripts, participant interviews, written documents and direct observations. The results reveal a marked difference in the content and timing of discussions over the life of each group project, strongly supporting the hypothesis that system dynamics provides a better foundation for structuring discussions, eliciting mental models, and generating sound decisions.
This paper investigates the impact of speculative trading on foreign currency markets. A review of economic literature reveals that there is still no agreement to whether speculators amplify or tame fluctuations of exchange rates. Relevant system dynamics literature suggests that trading by speculators contributes to the formation of price bubbles. However, very few system dynamics papers exist that analyze financial markets at the micro-level of traders. Hence, we turn to the field of computational economics and adapt a well-known heterogeneous agent model. Our new system dynamics model is used to analyze the role of speculation in foreign currency markets.
This paper presents an interactive simulation of the effects of emissions and absorptions of anthropogenic carbon dioxide (CO2) in the atmosphere. The interactive simulation based on the bathtub metaphor, was built using the Dynamic Integrated Climate Economy model (DICE)-1992. The interactive tool allows participants to make decisions on the anthropogenic CO2 emissions, observe the consequences of the decisions and try new decisions. In a laboratory experiment, we tested the participants ability to control the CO2 concentration to a realistic amount in the atmosphere over a period of 100 to 200 years. Participants worked on one of two extreme conditions: one rapid, where transfer rate of carbon dioxide was 1.6% per year with CO2 emission decisions made every 2 years, and other slow, where transfer rate of carbon dioxide was 1.2% per year with CO2 emission decisions made every 4 years. Due to human incapacity to handle feedback delays and their use of faulty heuristics, we expected participants to find the slow condition harder to control as compared to the rapid condition. Results show that participants had more difficulty achieving control of CO2 concentration to goal in face of slower dynamics than rapid dynamics. Implications and future of our research findings are discussed.