The Norwegian Armed Forces used to have a unitary personnel policy. All officers were recruited with prospects of life-long employment. The long time constants in such a system meant that a transformation into a younger corps was almost impossible to achieve. The model-supported intervention significantly reduced the probable risk of failure in policy design and implementation. A number of achievements must be attributed to the model intervention per se. First, the models base case projected a 100% surplus of senior officers. This was an eye-opener. Moreover, the lack of suitable options within the current policy regime became obvious. Finally, the suitability of the new policy was convincingly presented and its implementation success virtually secured. The success of the model intervention is discussed. Though the most aggregated model sufficed analytically, the existence of a more detailed model that reflected the production system, crucially enhanced the analysis face validity, especially as a cost analysis was called for. However, more critical than the models transparency was that the results fell within the comfort zone of most key stakeholders. The results challenged intuitions enough so that the model was considered invaluable, but not so much so as to question the approach.
The Military Roundtable is the arena for sharing ideas and experiences
on the application of System Dynamics to military problems. The list of
topics includes, for example: strategy development; force-on-force
analysis; war-gaming; military decision making; training of military
decision makers; including command-post exercises; preparedness studies;
human resource management; development and management of military
capability; management of materiel acquisition; military logistics
modelling; in-service management. We suggest the following main topic
for this year's meeting: "SDM as a tool to support training and
exercise". Opportunities exist for participants to provide update on
recent research and consulting activities, to discuss opportunities for
the future and challenges that confront those working in or having an
interest in system dynamics modelling (SDM) in military context. We will
continue the work on assembling a compendium of models and readings on
SDM in defence.
In this poster, authors explain a System Dynamics model developed for measuring efficiency of the Small Aircraft Transportation System (SATS) that NASA has been developing to enhance intercity travelers' mobility in the country. The model is comprehensive in the sense that it includes multi-modes such as automobile, commercial airlines and rail. It also considers different types of decision makers such as travelers, airlines, Federal Aviation Administration (FAA) and Federal Rail Administration (FRA) that dynamically interact with each other based on its own interest. The model allows users to change several critical but uncertain parameters such as the price for SATS trip, airports for SATS operations, etc. This feature enables users to do "what-if" type of study. Technically, the model is developed as a stand-alone tool with a Graphical User Interface that encloses all computational procedures written in MALTALB. Socio-economic data and computational results are represented at a county level using the Geographical Information System (GIS).
The automotive industry is considered as one of the main drivers of todays global economy. The industry spans across the globe, with nearly each country trying to develop the industry and its supply chain within its boundaries. This paper presents a Business Dynamics model that maps the Egyptian Automotive industry, which started as a public industry and then transformed to a market driven private industry. The Egyptian automotive industry focuses on the local Egyptian market, with no current plan for exporting to the global market. Such focus provides the Egyptian automotive industries with challenges that impede its growth. The Business Dynamics model presented in the paper presents an explanation of the current status of the Egyptian Automotive industry. The model is then used to provide insights for the current status of the industry, as well as testing several policy options for stimulating the industrys growth.
Modelling of technology adoption has tended to be based on individual product diffusion, although traditional models have been extended to incorporate replacement, competition, generations of substitution and other managerial variables such as pricing. A question is: how can these models be broadened to represent service industry applications and generalised or upscaled to model the phenomenon of General Purpose Technologies? GPTs have the properties of pervasiveness and complementary technologies. GPTs suffer from long development delays or start-up problems involving the co-ordination problems of complementary bandwagon behaviour. System dynamics modelling is proposed as an effective industry-level modelling approach to link standard expert judgement market forecasting used in industry and theoretical analysis used by economists in order to provide robust technology management policies. This paper represents an overview of the work-in-progress research themes and a modelling agenda.
An Adaptive Expectations Approach to the Mechanisms of Transmission Model of the Central Bank of Colombia
Fernando Arenas Pontificia Universidad Javeriana
Franz Hamann Banco de la República
ABSTRACT
Looking for the potential applications of system dynamics in macroeconomic modeling at the Central Bank of Colombia, the Mechanisms of Transmission Model (MTM) was recast in a system dynamics model. The forward-looking function of the model that, in the case of the MTM is a rational expectations based function, was approached by means of the TREND function. This document describes the system dynamics model and shows comparative impulse-response results between the models, when PULSE and STEP shocks are applied to inflation target, monetary policy, food supply, nominal depreciation rate, and risk premium.
This paper examines results on a series of Cournot markets with groups of five seller subjects. Step by step, we add complexity (and realism) to the simplest market and test the effects on behavior in an accompanying laboratory experiment. Consistent with previous experiments and the rational expectations hypothesis, price behavior was explained with Cournot Nash equilibrium with biases towards competitive prices. When complexity is increased, there rationality is degraded and lead to a salient cyclical tendency. Indications of cyclical behavior were induced by the application of spectral analysis and autocorrelation. We found that the more problematic effect of complexity in market behavior is the extra delay rather than accumulations. We proposed a heuristic based on the bounded rationality theory, but the tests were not satisfactory.
A key determinant of any groups performance in such contexts as varied as product development, consulting, and craft manufacturing is its transactive memory system (TMS): that is, its shared, tacit memory system for managing and communicating information relevant to the group. Using the methodology of system dynamics, we model the relationship between TMS and productivity by leveraging the theory of learning-by-doing at both the group and individual levels. We also incorporate into the model the concepts of group forgetting, in which employee turnover reduces group knowledge. We also include the effects of specialization, overspecialization, and knowledge obsolescence. We then simulate the impact of each of these refinements and perform sensitivity analyses on them. Finally, we discuss several implications of this model for future research. One implication is that representing group learning processes by a single, traditional, power-law learning curve may be in many cases inadequate. Another is that the very development of a TMS may create excessive individual specialization that is detrimental to future productivity levels.
Demand Conditioning is one of the methods used to address imbalances between supply and demand in supply chains. This requires the manufacturer to adjust the demand plan to respond to supply issues. The supply chain has several sources of delays and uncertainties such as lead times at different stages, forecast error, supply yield variability etc. that could potentially trigger or influence the conditioning process. In this paper, we examine dynamical effects in the conditioning process to study potential instabilities. We developed a Systems Dynamics model of a PC manufacturing supply chain to examine instabilities in the supply chain. This model provides insight on supply chain risks and error propagation due to unsynchronized execution. We also use the model to study the effect of different countermeasures to stabilize the supply chain.
Prices in the Property and Casualty Reinsurance market are known to undergo significant fluctuations. In order to understand the reasons for these fluctuations a simulation model was built that replicates relevant features of the reinsurance market: a limited number of market participants are competing, low product differentiation, volume constraints for each market participant and discrete volume decisions based on estimated rather than actual market prices. Despite a number of simplifications the model captures the current market dynamics. In a further development the model was made interactive allowing actual players to take the role of the reinsurance companies and make the individual volume decisions based on current financials and the market history.
The model was built using agent based instead of system dynamics modeling techniques particularly to simplify implementation of critical discrete events and to create a simple to understand structure.
We will discuss the model, the trade-offs between the Agent-based and System-dynamics approach as they applied to this model and share some experience in communicating the model structure with the business owners.