Behavioral Modeling and Simulation From Individuals to Societies (2008) / Chapter Skim
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Part II: STATE OF THE ART IN ORGANIZATIONAL MODELING, Part II: State of the Art in Organizational Modeling
Part II: STATE OF THE ART IN ORGANIZATIONAL MODELING, Part II: State of the Art in Organizational Modeling
Pages 89-96
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Part II STATE OF THE ART IN ORGANIZATIONAL MODELING 89
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The diverse expertise of the committee members contributed greatly to the completeness of this review but also made it challenging to agree on an organizing framework for presenting the review results. Refined through multiple iterations, the organizing framework that we developed represents a significant product of the study.
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Then, an aggregate proximity matrix X, whose rows and columns corresponded to "kinds of models," was constructed such that each cell Xij of the matrix recorded the number of respondents that placed the ith kind of model in the same pile as the jth kind of model. The final step was to visualize this proximity matrix using a standard network visualization package called Netdraw (Borgatti, 2002)
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Multiagent Representative_agent Simulation Cellular_automata Multiagent_network Agent-based Social_network Computational Dynamic_network Process System_Dynamics Dynamical_systems Mathematical Differential_equation Markov Difference_equation Linear Time_series Multiattribute Nonlinear Statistical Cultural Equilibrium Group_decision-making Organizational_culture Econometric Organizational_learning Input-Output Cognitive Game_theory Optimization Machine_Learning Genetic Influence Expert_systems Risk Behavioral Conceptual Decision_theory 93 FIGURE II-1 Perceived similarities among types of models. Part II-1.eps broadside
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Finally, as noted at the bottom left, three model types -- influence, behavioral, and conceptual -- did not cluster with other types. Four-Part Organizing Framework for Models On the basis of the empirical clustering results described above and further discussion, the committee developed a four-part categorization for reviewing modeling approaches: (1)
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Agent-based models, and to some extent game theory and network models, achieve this double linkage. Yet only recently have researchers begun to create hybrid models that include agents who employ sophisticated psychological models and whose macro effects link to a system dynamics model.
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Gaming, the creation of an environment in which real people can play against one another or against artificial players, can be thought of as a methodology, but as these gaming models apply many of the other types of models, and as they involve people interacting with the games, we set them apart. Online gaming environments are both consumers of models -- to create artificial players and the social effects of player actions -- and potential testbeds for generating data to develop and test models of the communications and actions of large numbers of individuals interacting in a simulated world.
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