STRATEGIC CONTROL AND INTERESTS, ITS EFFECTS ON DECISION OUTCOMES

In political systems and large organizations, ultimate decision makers are usually just a small subset of all actors in the social system. T o arrive at acceptable decisions, decision makers have to take into ac count the preferences of other actors in the system. Typically prefere nces of more interested and more powerful actors are weighted heavier than those of less interested and powerful actors. This implies that t he total leverage of an actor on the decision is determined by the com bination of his power (his potential) and his interest (his willingnes s to mobilize his power). As the exact level of an actor's leverage is difficult to estimate for the other actors in the system, an actor is able to optimize his effects on outcomes of decisions by providing st rategic information. In this paper, first an analytic solution is pres ented for the optimization of strategic leverage in collective decisio n making by one single actor. In this solution, the actor makes assump tions about the leverage other actors will show in decision making. Su bsequently, the actor optimizes the outcomes of decisions by manipulat ing the distribution of his leverage over a set of issues. The analyti c solution can be theoretically interpreted by decomposing the solutio n into three terms, the expected external leverage of the other actors on the issue, the evaluation of the deviance of the expected from the preferred outcome of the issue, and the restrictions on the distribut ion of leverage over the issues. The higher the expectation of the lev erages the other actors will allocate to the issue, the less an actor is inclined to allocate leverage to the issue. The higher the evaluati on of the deviance, the more an actor is inclined to allocate leverage to the issue. This is restricted, however, by the required distributi on of leverages over the issues. The researcher is able to manipulate these restrictions to investigate its consequences for the outcomes. I n the next step, we investigate whether we can find a Nash equilibrium if all actors optimize their leverage simultaneously. Under certain c onditions, a Nash equilibrium can be found by an iterative process in which actors update their estimates oh each other's leverages on the b asis of what the other actors have shown in previous iterations. Appli cation of the model to artificial data shows that actors with strong p references in the center have more possibilities to realize good outco mes than other actors. On the basis of an empirical application it is shown that a Nash equilibrium does not always arise after a large numb er of iterations unless actors have learning capabilities or are sever ely restricted in their strategic behavior.