Behavioral Modeling and Simulation From Individuals to Societies (2008) / Chapter Skim
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4 Macro-Level Formal Models
4 Macro-Level Formal Models
Pages 122-148
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From page 122... ...
Each car would have (a) two states: a speed and a he T use of differential equations reflects the history of system dynamics modeling and its roots in electrical and mechanical engineering and control systems theory.
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From page 123... ...
of acceleration, determined by the driver's application of the gas or brake pedal; and (c) a single output, the position/location down the road. Simple differential equations, based on the laws of physics (and the vehicle acceleration/braking d ynamics)
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From page 124... ...
Generally, differential equations serve as the basis for a block's dynamics, but it is straightforward to elaborate, via either the addition of subordinate blocks as just described or the addi tion of, for example, nonlinear characteristics (e.g., a limit on the acceleration obtainable via a fully pressed-down gas pedal in the above example)
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. In essence, Forrester transformed the generic nth order differential equations characterizing general system dynamics theory into n first-order differential equations that are intuitively simple to understand and, via the associated programming language Dynamo, into a transparent graphic representation of the key interrelationships among variables (Richardson and Pugh, 1981)
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µn (t ) : Average rate of population growth (the difference dt between the total average birth rate and death rate)
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. The structure of system dynamics models can be characterized by four hierarchical levels, as shown in Figure 4-2.11 All interactions and impacts ot N explicitly shown is how the flows are influenced by the stock levels.
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. A more detailed description of system dynamics modeling and the equations it uses is available in Sage (1977)
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, because of the glaring mismatch between model "predictions" and what was actually occurring on the world stage. This became more apparent as time went on, and it is fair to say that this failure to meet empirical validation standards considerably dampened the initial enthusiasm that met the system dynamics viewpoint toward understanding the complex interrelations of complex systems.12 12 owever, system dynamics modeling has been applied to several other areas, including H software project dynamics (Abdel-Hemid and Madnick, 1991)
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interactions. It is not our intent here to survey all of these efforts, but merely to provide a few illustrative examples to indicate the potential of system dynamics modeling in this area.
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One of the approaches, led by Nazli Choucri, developed a "state stability model" using a system dynamics approach; a high-level view of the model is given in Figure 4-5. Power Industrial Oil Oil Power Substation Water Plant Field Refinery Generators Industrial Refined Power Crude Water Fuel FIGURE 4-4 SROM infrastructure model.
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18) , it "shows loads, demands and stresses on state and the causal dependencies; shows feedback loops, tipping points and unintended consequences; [and]
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. Environments for System Dynamics Modeling The earliest computer-based system dynamics simulations were created by Richard Bennett, who developed the SIMPLE (Simulation of Industrial Management Problems with Lots of Equations)
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does not make it so. There are such things as accounting identities, but mathematically exact descriptions of social or h uman processes generally do not exist." We agree, but, of course, this is not a shortcoming that is specific to computational models built on system dynamics concepts; it is a general issue with any "model" that can be reduced to executable software.
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Organization theory is a study of the structure, behavior, and performance of the organization (Scott, 1998) in order to describe, explain, and predict.
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For both approaches, there is an emphasis on the data gathered from organizations using an inductive approach for understanding. There has been a smaller effort on formal mathematical modeling of organizations using a deductive approach, in which the analysis of the models yields insights and hypotheses that can be tested using field or lab data.
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First, a simulation model of an organization, which includes its structure and agents, generates behavioral and performance data on the organization, which can be analyzed as if they were field data.14 These are frequently called virtual experiments. Agent-based models explicitly model both the agents or individuals and the decision-making structure of the organization, which includes the communication and authority links among the agents.
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We begin with the theory models and then consider the design models, with comments when the models can be used both ways. Organization Theory Models There are numerous organization simulations or computational organizational models; here we review a few of them.
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The set of theories that are unified into a single computational theory of organizational behavior interact in complex fashions to determine the overall level of organizational performance. Harrison and Carroll (1991)
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. NK models have been applied to organization theory questions of adaptation (Levinthal, 1997)
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SimVision was applied to investigate organization theory questions. But it was originally created as an organizational design tool to help p roject managers optimize projects and project management implementation (Levitt, 2004)
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Construct, referred to earlier, has also been used to evaluate various organizational designs under different turnover regimes. Moreover, when data are collected on the who, what, where, and how of organizations, such data can first be assessed for points of vulnerability in ORA and then Construct can be applied to the same empirical description of the real organization to forecast its behavior in terms of information diffusion and performance with or without turnover (Carley, Diesner, Reminga, and Tsvetovat, 2005)
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Challenges and existing approaches for developing such integrated multilevel models are discussed in Chapter 8. Finally, innovative experimentation approaches are needed to advance the state of the art in organizational modeling.
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Computational and Mathematical Organization Theory, 9(2)
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. Fallacies of fast track heuristics: Implications for organization theory and project management.
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Computational and Mathematical Organization Theory, 8(4)
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. Intro duction to computer simulation: A systems dynamics modeling approach.
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. Modeling complex projects.
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