From the Margin to the Mainstream: an Agenda for Computer Simulations in the Social Sciences

FROM THE MARGIN TO THE MAINSTREAM: AN AGENDA FOR COMPUTER SIMULATIONS IN THE SOCIAL SCIENCES Erhard Bruderer The University of Minnesota Carlson School of Management and Martin Maiers The University of Minnesota Department of Computer Science Computer simulation has had a long and established tradition in the social sciences. Unfortunately, research in this field has always been at the margin. Why? After all, computer simulations allow us to make rigorous models of complex social processes which are not accessible to mathematical modeling. This paper explores why we failed to have a major impact on the social sciences. However, there is good news on the horizon which is likely to change our fate. Among the most important changes are the development of the Internet and the emerging standard of the computer language Java. We argue that in the future the Internet and Java will make computer simulation easily accessible to many social scientists and thus will spur high growth in its use. In this paper we outline a specific and practical agenda to move computer simulation from the margin into the mainstream of social science research. We conclude that 30 years from now, computer simulation will be a mainstream research tool in the social sciences as much as advanced statistics is today. AN ADAPTIVE SIMULATION APPROACH FOR INVESTIGATING INFORMATION PROCESSING STRUCTURES IN ORGANIZATIONS Roger M. Stein Leonard N. Stern School of Bus New York University and Moody’s Investors Service and Robert N. Bernard Department of Urban Planning Rutgers University and Coopers & Lybrand Consulting We adopt the view of organizations as information processing entities. We present a methodology for modeling organizational structures and for determining which organizational structures, if any, distinguish themselves given various constraints. As such, we propose that various exogenous and endogenous factors should affect the performance of organizations with respect to information processing tasks. To test our propositions we implement a simulation methodolgy. Our methodology relies heavily upon combining Monte Carlo methods and genetic algorithms to represent dynamic organizational operating environments and competition among firms, respectively. We present examples of the organizational computer model and demonstrate results of the methodology for testing our underlying propositions. We feel the contribution of our work is not so much the valdiation or rejection of specific propositions, but rather the introduction of a new tool for validating entire classes of organizational prosositions through simulation. The reimainder of this extended abstract foucuses on an overview of this methodolgy. Organizations presumably do not know the functional form of their information processing dynamics. As such, we postulate that organizations perform a type of trial and error search for effective structures. Simulation methods allow us to mimic this search process and test the propositions while making only a limited number of assumptions about the parameters of the problem. They also allow us to deal with the complexity inherent in organizational structures. Finally, simulation allows us to create an environment in which differing organizational structures compete with each other to efficiently perform similar tasks. We have created a generic toolbox, called OrgNet, for representing organizations. The toolbox is an object library written in C++. The toolbox allows us to represent organizations, their members, and their structures. The object library represents organizations' members as having a fixed amount of memory, a particular computing speed, a task function, and a message queue that holds input information that the member receives. The organization itself is composed of a number of members and a matrix which defines the various types of relationships among the members. The computing speed parameter indicates how many units of time the member requires to execute its task function. The task function itself defines how the member processes the information in its message queue. The message queue serves as a post-office or clearing house for information. Members communicate with each other by posting an unambiguously addressed message to the message queue. The organization coordinates delivery of these messages to its members. Finally, the organization has a clock which synchronizes the activity of the organization members and message delivery. Each message is time-stamped with its scheduled delivery time and is delivered at the time indicated.