OPTIMIZING UNIVERSITY ADMISSIONS PLANNING

The crucial issues in the administration of higher education embody the very purpose, function, and concept of each institution. The institution's administrative policies are based on the combined philosophy of many conflicting interest groups such as taxpayers, donors, administrators, faculty, students, staff, and users of university services. A function performed by the university which is receiving increasing attention and outside pressure is the formulation of admissions policy for newly entering students. This paper investigates problems involved in the admissions planning and presents a goal programming model as an optimization tool for the problem.     

PSYCHOLOGICAL DETERMINANTS OF BOUNDED RATIONALITY: IMPLICATIONS FOR DECISION-MAKING STRATEGIES

In this paper the implications of cognitive strain for decision-making effectiveness are explored. Literature concerning the psychological processes of decisionmakers which underlie the operation of cognitive strain and which predispose them to the effects of cognitive strain, is reviewed. Next, the impact of cognitive strain on narrowly constraining or “bounding” rational decision-making is examined, and the choice strategies of satisficing and incrementalizing are criticized as failing to broaden the bounds of rational decision-making. Finally, elements of an eclectic choice strategy designed to assist decision-makers handle the informational demands of complex decision problems are discussed.     

AN EMPIRICAL EXAMINATION OF SOCIAL POWER IN TERMS OF DECISION THEORY1

The paper presents an extension of decision theory to the analysis of social power. The power of a person, A, over another person, B, is viewed in terms of the effect A has on B's decision. The analysis is based on the idea that B's decision regarding the performance of alternative behaviors is a function of 1) B's utility for the consequences of the behaviors and 2) B's subjective probabilities that the behaviors will lead to these consequences. In these terms, A's power over B lies in A's ability to mediate various consequences for B, contingent upon B's compliance or noncompliance. Subjects were asked to consider eight situations in which hypothetical individuals had to make a choice between two courses of action. In each situation another person (A) was attempting to induce the hypothetical individual (B) to choose one of the alternatives, while various situational factors were influencing B to choose the other alternative. The subjects were asked to consider B's utilities and subjective probabilities in each situation and to indicate whether or not B should comply with A and to make ratings of A's power. The decision theory analysis did well in predicting whether or not subjects would indicate that B should comply with A. Also, subjects generally were able to correctly specify whether A or the situational factors had more influence over B's decision. Finally, the subjects' ratings of A's power in the eight situations were highly related to the decision theoretic measure of power.     

Effects of Hourly,Low-Incentive,and High-Incentive Pay on Simulated Work Productivity: Initial Findings With a New Laboratory Method

The failures of previous studies to demonstrate productivity differences across different percentages of incentive pay may be partially due to insufficient simulation fidelity. The present study compared the effects of different percentages of incentive pay using a more advanced simulation method. Three payment methods were tested: hourly, low-incentive, and high-incentive (0%, 10%, and 100%) pay. Four participants performed a simulated work task for 30 6-hr sessions. Productivity under the 100% incentive condition was consistently higher than under the 10% condition for all participants. Productivity under the 10% condition was higher than under the 0% condition for two participants. Results suggest that different percentages of incentive pay may in fact produce productivity differences under more realistic simulated work conditions.     

Median treatment effect in randomized trials

For two response variables y _t and y _c corresponding to two treatments for two policies) T and C , we wish to learn about quantiles of y _t− y _c from the marginal quantiles of y _t and y _c; only one of y _t and y _c is observed for an individual. We find that, in general, this is difficult for quantiles other than the median unless strong assumptions are imposed on how y _t is related to y _c. For the median, we present conditions under which the sign of the median treatment effect is identified.