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.
Evaluating new bank loans has been considered as one of the main dilemmas that banks managers have to deal with in order to reduce the probability of default. The lending process is a series of activities involving two main parties whose association ranges from the loan application to the successful or unsuccessful repayment of the loan. This paper describes the construction of a flight simulator which uses the ideas of System Dynamics and the Viable Systems Methodology. The Decision Support Tool thus formed uses systemic approaches to measure a firms performance and can provide a risk assessment in the sense of evaluating performance under different (what- if) scenarios. The credit worthiness from this model can then be evaluated against the usual estimate based only on financial ratios.
Despite the fact that much of recent terror is ethnically based, little attention has been paid to systematically explaining ethnic violence. We build on the work done by the Minorities at Risk Project (MAR) to the issue of ethnic terror using systems dynamics. While there has been important work done using MAR to explore ethnic violence as a base using statistics and qualitative analysis (Gurr 2000) there has been little work exploring ethnic terrorism specifically and none that has exploited systems dynamics as an analytical tool. The application of a systems dynamics approach will help us go beyond some of the limitations of statistical analysis to explore how government policy and ethnonationalist terrorism feed of each other in a cycle of violence, discrimination and repression. This work has three broad goals. First, it is targeted at understanding the causes of ethnic terror and second examining the way the relation between the ethnic policies of governments and the behavior of ethnic groups - particularly their choice to use or not use terrorism relate systematically. Third, this work sees to apply for the first time the tools of systems dynamics to political violence.
The glucose regulatory system in man is a complex system. It is a nonlinear, multiloop, self-regulatory feedback system which exhibits behavior which is often counter-intuitive and which is insensitive to many external interference. The challenge in this work is to employ a model that is simple, but not too simple for the students of first medical year with the purpose to help them understand the glucose regulatory system in the human being body by quasi-practical approach based on simulation tool and not my theoretical understanding. This model describes the carbohydrate metabolism, digestion, absorption and fate of intake carbohydrates. The model attempts to reflect the underlying (patho) physiology of insulin action and carbohydrate absorption in quantitative terms such as insulin sensitivity, volume of glucose and insulin distribution and maximal rate of gastric emptying. The model represents the integration of two existing models proposed earlier by Foster et al. (1970) and Lehmann et al. (1992).
The paper addresses the question whether a modular organizational structure breeds mechanisms that promote proactive strategic flexibility. We examine this question from the perspective of the cognitive school of strategic management and with the aid of system dynamics modeling and simulation to explore long-term dynamic effects. Both our analysis and our experiments with the model suggest that modular organizations do not necessarily encourage the construction of managers mental models with a capability to generate more strategic options and, thus, do not promote strategic flexibility at a higher degree compared to more traditional organizational structures.
The purpose of this research was to assess the Egyptian software industry using a Systems Dynamics approach based on the Software Export Success Factors Model developed by Heeks and Nicholson, 2002. A CLD was prepared as a step towards building a model to simulate the expected effect of key software-related infrastructure variables on the Egyptian software export revenue. Simulations of software export industry over a period of 10 years point to the following: (1) Injecting an additional 30% financial resources resulted in an increase of 8.4% in software export revenue and 2.1% in job opportunities with respect to the reference mode, (2) Improving IT staff productivity by 42%, and delivered software quality by 10%, with a decrease in resistance to change of 20% led to an increase of 68.7% in software export revenue and of 12.9% in job opportunities with respect to the reference mode, (3) Enhancing R&D by 50% and IT staff innovation contribution by 10% resulted in an increase of 14.4% in software export revenue and 3% in job opportunities with respect to the reference mode, and (4) Improving the software export promotion efficiency by 14% and quality of delivered software by 10% led to an increase of 38.7% in software export revenue and 8% in job opportunities with respect to the reference mode.
The method presented in this paper allows for an investigation of how the eigenvalues characterizing the model behavior is created from the underlying model structure and how this behavior feeds back to change instantaneously the relative significance of the model structure. The method also allows us to identify the relative significance of the various parameters that governs the gains of the links and loops of the model. The method has been implemented using Matlab software for the purpose of facilitating an eigenvalue analysis of system dynamic models. This work is based on control theory as well as the previous work on eigenvalue analysis in system dynamics. It summarizes the thesis work by Ahmed AbdelTawab AbdelGawad (2004) and Bahaa E. Aly Abdel-Aleem (2004), under the supervision of Mohamed Saleh and Pål I. Davidsen. The method outlined and Matlab code developed in preparation for this paper may be implemented as part of any simulation package.