Structure is a critically important determinant of system behaviour. The relationships between the most basic elements (accumulations, physical flows, information flows, feedback and delay) found in system dynamics models and the building blocks of system dynamics structure are examined. Complexity is explained. The complexity of models we might build, relative to real-world complexity is examined. Why we need to approach model building top-down rather than bottom-up is explained. How to design system dynamics group model building projects through a top-down approach is explained. How to decompose conceptual models developed top-down into appropriate modules to be constructed then synthesised bottom-up is explained. Attendees will design a group model-building project using this approach. The relationships between model functionality, verification, the model as a necessary and sufficient representation of the real world, and the real challenges of validation are explained. How to build models and design effective test to ensure those models work as intended is explained and demonstrated. How to build models using a methodology integrating aspects of systems thinking, system dynamics modelling and engineering is demonstrated. How to manage the complexity of the model through each stage of development is explained..
System dynamics is still evolving. This paper argues additional rigour is needed if system dynamics is to achieve its full potential in helping us understand complex behaviour of human activity systems. It argues that a detailed appreciation of how systems engineers define, analyse, specify, manufacture, operate and support complex systems could inform the evolution of system dynamics even though there are significant differences between the two disciplines. The proffered approach integrates systems thinking, system dynamics modelling and systems engineering. This integrated approach enables group model building and building of exceedingly complex models through top-down design and careful management of the complexity introduced at each stage of the model-building process. The approach promises to engender greater confidence that models developed using it work and are both necessary and sufficient representations of the real world. The greatest potential gain accruing from application of this methodology is enhanced acceptance of system dynamics.
Project based organizational structures are utilized in many industries. The firms engaged in these endeavors, project sponsor and contractor alike, risk both capital and reputation in the market-place with each new project. The relationship between project sponsor and contractor influences the outcome of the project to a significant extent. Complex and challenging projects are made more so by the adversarial relationships that frequently exist between the sponsor and contractor(s). This paper presents a model for examining the influence of the contractor/sponsor relationship on the execution of a project. The focus is on the effects of the relationship, as determined by the financial performance of the engaged firms and key project performance indicators (schedule, budget etc), on the degree to which the firms engage and the impact this has on project performance. Analysis of the model indicates the importance of appreciating the projects need for effective team integration in determining the financial arrangements.
Medication errors in hospitals are a large and increasing problem, which has traditionally been considered a result of human error. Recent attempts to reduce errors have emphasised systems approaches and improvements in information and communications technologies (ICT). As part of a multi-method evaluation project for hospital point of care clinical systems, we assembled a team of professionals from a variety of clinical, information management, health management, sociology, linguistics and engineering backgrounds. We built a systems simulation for explicitly representing the interactions among the key determinants of medication errors. These included the complex interactions of patients and staff, information, medications, work practices and the infrastructure and policies within a hospital environment.
Our team simulated hospital inpatient and staff flow, generation and interception of medication errors, and the potential impacts of ICT-enabled work practice changes. This paper describes the System Dynamics Model of long-term context that produces errors in the medication management process. Future extensions include the use of a combined agent based and SD simulation to produce a multi-method, multi-level systems simulation testbed as an integrating framework for evaluating combinations of improvement interventions.
KEYWORDS: health systems simulation, medication error, information and communications technology, multi-method evaluation
This research tries to offer a design of the cash waqf management system in a system dynamics model. The Cash Waqf Management is expected to become one of the alternative instruments for the poverty alleviation programs in Indonesia. These programs require huge amount of fund that cannot be provided thoroughly by the government. Therefore, initiation of new sources of fund for such a program is inevitable. In the Islamic sosio-economic concept, there is a source of social fund that is economically and politically free of charge, namely cash waqf. In this concept, Nadzir (cash waqf fund manager) collects the fund from Waqif (cash waqf payer) and invest the money in the real sector and in any syariah-based investment opportunities. Nadzir could allocate profits and returns gained from the investments to poverty alleviation programs. Nadzir is obliged to maintain the amount of fund in such a way that it does not go below the initial amount. Therefore, Nadzir not only should be highly capable, but also needs an experienced financial institution in helping SMEs development efforts. Using the system dynamics methodology, we tries to know the structure of cash waqf system and simulate the behaviour of cash waqf model.
This paper uses a system dynamics model to analyze rule compliance in organizations. The analysis takes securities regulation as an illustrative case but applies to other private, nonprofit, and public activities complying with rules overseen by external bodies in the course of producing goods and services. We consider how three levels of behaviorproducers, internal organizational controllers, and external regulatorsinteract in shaping compliance with rules.
This paper explores the history of the Beer Game, its rules, and lessons. By triangulating information from the literature, archival analysis, and interviews with experts in the field, we have identified the main changes in the game over its almost 50-year history. Additionally, an exploration of possible changes to the game and new games in the field of system dynamics are examined.
This paper describes a systems dynamics model that reflects the possibility of having three levels of complexity together and articulated on a synchronous synergy of all relevant participants of value added systems: the activities at the firm level, networks of industries, and supporting organizations at the regional level. Following a systemic approach, we have identified eight parameters to measure the attractiveness effect of a region: Clustering and associativeness, Value added, Differentiation value, EVA, Attractiveness leverage, Global market coverage, Innovation and Social Capital. Based on these indicators, we have developed dynamic models for emergent industries which have uncertain trends and no previous regional developments. At this moment we are working on models for the Software, Biotechnology, Aerospace and Autoparts Industries that are currently in the process of clustering in the State of Nuevo Leon (Mexico).
In the article we address recurring causes of failures in starting up a new company. In particular, we explore flaws in entrepreneurs mental model when dealing with feedback and delays in building up stocks of assets. The work that we are presenting is in progress but scored the following targets. First, under a theoretical point of view, we laid down borders to define a theoretical territory where the strong connections can be observed that entwine literatures on start-up, on the resource-based view of the firm and system dynamics. Second, we created an experimental laboratory to test individuals recurring mistakes when dealing with a start-up.
Further developments of this work are in the direction of setting an experimental protocol to conduct empirical research on a sample of players.
A system dynamics model was developed to help hospitals assess their ability to handle surges of demand during various types of disasters. The model represents all major flows of patients through a hospital and indicates how specific responses to a surge may ameliorate bottlenecks and their potentially harmful effects on patients. The model was calibrated to represent a specific hospital in West Virginia and was tested under three quite different surge scenarios: a bus crash, a chemical plant leak, and a SARS outbreak. Under the difficult conditions of the SARS scenario, avoidable deaths of patients awaiting emergency care could be effectively reduced by adding reserve nursing staff not in the emergency department, as might be expected, but in the overloaded inpatient wards. The model can help hospital planners better anticipate how patient flows may be affected by disasters, and identify best practices for maximizing the hospitals surge capacity under such conditions.