The integrated use of enterprise and system dynamics modelling techniques in support of business decisions

Enterprise modelling techniques support business process re-engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulationmodelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink

Using simulation to evaluate investment projects

The goal of this paper is to show how the system dynamics simulation can be applied to incorporate in the evaluation process of various investment projects the interactions between market demand and financial health of the firm. Through simulation, a more accurate representation of the variability and uncertainty of business proposals or strategies can be obtained.simulation, system dynamic, investment decision

Teaching the dynamics of the growth of a business venture through transparent simulations

Achieving rapid and sustainable growth is essential for business ventures to succeed. This being so, future entrepreneurs need to understand and manage the dynamics of business growth. Simulation-based learning environments (SBLEs) have been proposed as effective tools to help learners improve their understanding of complex business problems. However, previous research has found that learners tend to underestimate dynamic complexity. Transparent simulations allow entrepreneurship learners to explore the dynamic complexity of business ventures while accessing the model structure and growth behaviour. Previous studies have addressed some aspects of model transparency and produced inconclusive results regarding their impact on learning effectiveness. This study explores the learning and performance effects of using transparent simulations to teach the dynamics of the growth of a business venture. One such simulation experiment used a system dynamics model that represented the development of an energy service company (ESCO) venture under varying conditions of simulator transparency. Students who were subjected to the more transparent strategy achieved higher performance and demonstrated better comprehension of the business dynamics. However, our findings indicate that the effect to be gained from making only the simulator model more visible is more limited. The structural debriefing (focused on the critical variables and relations) was determinant in improving students’ learning regarding the stocks and flows structure in the prospects pipeline. Only after participating in the behavioural debriefing (focused on the relation between model structure, patterns of actions, and system behaviour), were the students able to appreciate the dynamics of the business feedback loops. The research suggests that educators who use complex business simulations should complement model transparency with structural and behavioural debriefings.info:eu-repo/semantics/acceptedVersio

Systems thinking activities used in K-12 for up to two decades

Infusing systems thinking activities in pre-college education (grades K-12) means updating precollege education so it includes a study of many systemic behavior patterns that are ubiquitous in the real world. Systems thinking tools include those using both paper and pencil and the computer and enhance learning in the classroom making it more student-centered, more active, and allowing students to analyze problems that have been heretofore beyond the scope of K-12 classrooms. Students in primary school have used behavior over time graphs to demonstrate dynamics described in story books, like the Lorax, and created stock-flow diagrams to describe what was needed to make a garden flourish. Middle school students have created larger stockflow diagrams to study how composting helps to reduce pollution and have created small simulations to study population dynamics and the spread of epidemics. High school students have created/used numerous computer models to study systemic problems in mathematics, physical science, physics, biology, environmental science, global studies, and history. Some high schools developed modeling courses allowing students to create System Dynamics computer models to study problems of their choice, write technical papers explaining their models, and present their models and model results to an audience. This paper contains explanations of some of the systems thinking lessons that have been used with precollege students, some for just 5–6 years (especially the primary and middle school examples), others (especially the mathematics and system dynamics model courses for high school students) for decades

Teaching system dynamics and discrete event simulation together : a case study

System Dynamics (SD) and Discrete Event Simulation (DES) follow two quite different modeling philosophies and can bring very different but, nevertheless, complimentary insights in understanding the same ‘real world’ problem. Thus learning SD and DES approaches require students to absorb different modeling philosophies usually through specific and distinct courses. We run a course where we teach model conceptualization for SD and DES in parallel and, then, the technical training on SD and DES software in sequential order. The ability of students to assimilate, and then put into practice both modeling approaches, was evaluated using simulation-based problems. While we found evidence that students can master both simulation techniques, we observed that they were better able to develop skills at representing the tangible characteristics of systems, the realm of DES, rather than conceptualizing the intangible properties of systems such as feedback processes, the realm of SD. Suggestions and reflections on teaching both simulation methods together are proposed. System Dynamics (SD) and Discrete Event Simulation (DES) follow two quite different modeling philosophies and can bring very different but, nevertheless, complimentary insights in understanding the same ‘real world’ problem. Thus learning SD and DES approaches require students to absorb different modeling philosophies usually through specific and distinct courses. We run a course where we teach model conceptualization for SD and DES in parallel and, then, the technical training on SD and DES software in sequential order. The ability of students to assimilate, and then put into practice both modeling approaches, was evaluated using simulation-based problems. While we found evidence that students can master both simulation techniques, we observed that they were better able to develop skills at representing the tangible characteristics of systems, the realm of DES, rather than conceptualizing the intangible properties of systems such as feedback processes, the realm of SD. Suggestions and reflections on teaching both simulation methods together are proposed

Developing a simulation model: The impact of seasonal demand fluctuations on dynamics of service business in Bergen, Norway

Masteroppgave i systemdynamikkGEO-SD351MASV-SYSD

Is Labor Supply Important for Business Cycles?

We build a general equilibrium model that features uninsurable idiosyncratic shocks, search frictions and an operative labor supply choice along the extensive margin. The model is calibrated to match the average levels of gross flows across the three labor market states: employment, unemployment, and non-participation. We use it to study the implications of two kinds of aggregate shocks for the cyclical behavior of labor market aggregates and flows: shocks to search frictions (the rates of job finding and job loss) and shocks to the return on the market activity (any factors affecting aggregate productivity). We find that both kinds of shocks are needed to explain the labor market data, and that an active labor supply channel is key. A model with friction shocks only, calibrated to match unemployment fluctuations, accounts for only a small fraction of employment fluctuations and has counterfactual cyclical predictions for participation.

"The Contributions of Professors Fischer Black, Robert Merton, and Myron Scholes to the Financial Services Industry"

This paper is written as a tribute to Professors Robert Merton and Myron Scholes, winners of the 1997 Nobel Prize in economics, as well as to their collaborator, the late Professor Fischer Black. We first provide a brief and very selective review of their seminal work in contingent claims pricing. We then provide an overview of some of the recent research on stock price dynamics as it relates to contingent claim pricing. The continuing intensity of this research, some 25 years after the publication of the original Black-Scholes paper, must surely be regarded as the ultimate tribute to their work. We discuss jump-diffusion and stochastic volatility models, subordinated models, fractal models, and generalized binomial tree models, for stock price dynamics and option pricing. We also address questions as to whether derivatives trading poses a systemic risk in the context of models in which stock price movements are endogenized, and give our views on the "LTCM crisis" and liquidity risk.