Mathematical and Computational Organization Theory Workshop April 22 and 23, 1995 Los Angeles, California Mathematical and Computational Organization Theory

s Mathematical and Computational Organization Theory LEARNING CONTROL IN DYNAMIC DECISION MAKING TASKS FAISON "BUD" GIBSON forthcoming SIMULATING THE IMPACT OF TECHNOLOGY ON INDIVIDUAL AND COOPERATIVE WORK DAVID KAPLAN Carnegie Mellon University dk3g+@andrew.cmu.edu http://www.cs. cmu.edu:8001/afs/andrew/usr/dk3g/www/homepage.html Through the use of the ARTORG (Artificial Organization) simulation the impact of technology on both individuals and cooperative work can be predicted. Existing technology such as two-way audio communicating device's as well as new technology for video and shared manuals are incorporated into the ARTORG. Flexibility of the simulation includes both the varied combinations of technology and the ability to accomodate a wide variety of tasks. Maurice Rojer Models of Collective Bargaining Processes Tested Maurice Rojer Maurice Rojer is a PhD student at Sociology Department, University of Amsterdam Oude Hoogstraat 24 1012 CE Amsterdam Netherlands Collective bargaining between organizations is a widely spread phenomenon. Bargaining takes place at different levels and in different contexts, such as international multi-lateral disputes, mergers between organizations, between employers and unions, between political parties in parliamentary decision making, etcetera. Several theories and models have been developed to understand, explain or predict outcomes of these interorganizational bargaining processes. Until recently, however, formal bargaining models were lacking any systematic account of the dynamics caused by interactions between bargaining organizations, or actors. The process is an important aspect of bargaining, though. Outcomes, whether optimal or sub-optimal, are the direct result of (inter)actions of bargaining actors, and are not the result of ex ante solution concepts. Solutions of, for instance, game theoretic bargaining models do not account for interactive dynamics. As far as theories do account for the process they do not pretend to be able to explain or even to predict outcomes of that process. Since 1985, two models have been developed in which the bargaining process is formalized and the bargaining outcome is predicted from the process. The first model, the so-called Expected Utility model by Bueno de Mesquita, treats collective decision making, or bargaining, as a conflictual activity. The second model, the Exchange or Logrolling model by Stokman and Van Oosten, emphasizes the cooperative nature of bargaining processes. Although both models approach the bargaining process in fundamentally different ways, they are directly comparable in their predictive and explanatory value. Both models are based on the same variables: the potential control of actors over outcomes, the salience of the issues for the actors, and the outcomes preferred by the actors. Thus, besides the fact that the bargaining process is now modelled, another benefit of these models is that they can be, and have been, empirically tested, even in different bargaining settings: the Expected Utility model has yet been tested on several international disputes, like the future of Hong Kong and the Israel-Arab conflict. Both models were also tested at the same occasion, in the context of a number of policy issues in the European Community. The latter test resulted for both models in correlations between predicted and actual outcomes of . 70. Although they seem to perform equally well, they make different predictive errors. The question remains which model performs the best in general. At the moment I test the models in a quite different institutional context: bargaining between organizations of workers and employers, resulting in collective agreements on labour relations and working conditions. The Dutch context, in which the models are tested, features plural representation (more than one union and/or employers' organization) and multi-issue bargaining. Thirteen collective agreements are analyzed which amount to 200 bargaining issues. A preliminary test of the Exchange model shows correlations between predicted and actual outcomes of . 74. Gabor Peli & Bart Nooteboom (University of Groningen, Faculty of Management and Organization, The Netherlands) Learning to Cooperate: the Simulation of Transaction Costs in Supplier-User Relations The present simulation model addresses issues of subcontracting: if producers do not possess all the necessary skills for production, then they may seek to employ suppliers who offer the desired complementary competences. The focus is on the dynamic issues of cooperation: suppliers adapt their competences to users' products, and users learn to absorb contributions from their suppliers. Transaction Cost Economics (TCE) is taken as a departure point, and it is extended with processes of learning and mutual adjustment between partners. The model is set up on the basis of movements in an Eucledian space. The dimensions represent the skills that a user intends to obtain by cooperation ("complementary competences"). The supplier's position shows the competence configuration it possesses. The user's position reflects cooperative abilities: it indicates the competence configuration that the user can best absorb at a given time. The smaller the distance between a source and a user, the better they complement each other (cognitive distance). So, the partners have to "learn" to cooperate, making efforts to get closer to each other in the competence space. Moreover, the competences also has to be adjusted to the product the partners intend to produce. Products is represented by the competence configuration by which they can be optimally produced (ideal point). Multiple technologies may allow for multiple ideal points for the same product. The simulation model assesses the advantages and drawbacks of having single/ multiple suppliers. The trade-off is evaluated in terms of characteristics like the speed of adaptation, accuracy of goal perception, consequences of defection, the frequency of product change. The results are demonstrated in a two dimensional space, in order to be able to plot movements visually. It is also shown that the "first mover vs. efficient production strategy" dilemma of traditional TCE can be obtained as a special case of the model. TRACKING AGENTS AND AGENT-GROUPS IN A DYNAMIC, MULTIAGENT ENVIRONMENT Milind Tambe Information Sciences Institute University of Southern California 4676 Admiralty Way, Marina del Rey, CA 90292