This study examines the effect of signals from a competitor on the decisions of managers in a situation of strategic interdependence. The context is a multi-period pricing simulation and the payoffs are structured in accordance with a Prisoner's Dilemma. The signals consist of messages from the competitor and observations of the pricing decisions made by the competitor. The managers' responses to particular types of signals and particular combinations of moves and messages change over the course of the simulation. Suggestions for future research on competitive signaling are offered.

The literature on the deomposition of mathematical programs as models for organizational design and resource allocation in decentralized organizations is extensive. Although models differ in detail, all conceptualize the allocation problem as a multi-level managerial coordination procedure, involving local (divisional) and global (organization-wide) resources, in which informational automony is to be maintained. That is, coordination of resource usage by relatively autonomous divisions is to be effected in these models without any one agent in the organization accumulating complete knowledge of the technical resource transformations, payoff or cost coefficients and detailed plans that divisions utilize in converting resources to useful ends. Unfortunately there has been little empirical investigation into the implementational problems of applying these models in decentralized organizations. This study reports on an experiment with human subjects as decision makers in a simulated decentralized organization. The formulation of the overall resource-allocation problem as a linear program permitted two forms of coordination: price-directive in which transfer pricing is used to allocate resources, and resource-directive in which a rationing or budgeting approach is used. Both schemes can be shown to solve the overall organizational problem but impose different information, communication, and decision-making structures upon the subject managers. The experiment was designed to examine comparative managerial performance by the subjects, as central coordinating agents, under the alternative transfer pricing and budgeting schemes. Within each of these schemes two levels of decision time pressure were also introduced to examine its impact upon subject performance. The purpose of the investigation was to study the influence of organizational design (allocation scheme) and situational factors (time pressure) upon human decision-making under carefully controlled experimental conditions. The experimental setting was that of a decentralized university incorporating three subordinate college divisions and one coordinating agent, the president's office. The colleges were modeled as linear programs and the coordination function was assigned to the experimental subjects. In the price-directive scheme a subject assigned a transfer price to each of two global resources in each planning iteration. In the resource-directive scheme a subject directly allocated amounts of the two global resources to each of the colleges in each planning iteration. Consistent with decomposition theory, feedback to the subject in the form of aggregate resource demands (price-direction) or individual bids for higher resource allocations (resource-direction) was given to initiate a new planning iteration. The budgetary goal utilized by subjects was to maximize net dollar contribution from colleges to the university under prespecified quality-of-education constraints. After several planning iterations each subject finalized the resource allocations, terminating the experiment. The hypotheses were that resource-directive subjects would outperform price-directive subjects, that high decision time pressure would exacerbate decision making and that subjects would outperform decomposition algorithms in early iterations. Data from the experiment did not support the first two hypotheses; the third was confirmed. Aside from concluding that strategic factors (organizational design) and tactical factors (time pressure) strongly influence decision making behavior, several specific implications can be tentatively drawn. In similar settings transfer pricing schemes may be preferable to traditional budgeting schemes for planning resource allocations. Furthermore, the potential exists for profitable use of man-machine procedures for resource allocation involving decision support technology in the form of decomposition models to augment human decision heuristics. Finally, experimental methods offer a vehicle for addressing human factors and implementational considerations missing from current analytic models.

The principal problem with Sidney's comments (and Maxwell's paper for that matter) is that the intermediate steps leading from the original problem formulation to the constraint (supposedly) obtained are not described.

An algorithm, computationally feasible for large problems, has been formulated for sequencing n jobs through a single facility to minimize the number of late jobs. This algorithm is then extended to solve the problem in which each job is associated with a continuous, monotone non-decreasing deferral cost function. The object is to produce a schedule where the maximum deferral cost incurred is minimal.

A location problem with a hierarchy of facilities and services is proposed and solved. The formulation defines a demand point to be covered for a given level of service if some member of the facility hierarchy eligible to provide that service is present within an appropriate distance. Furthermore, the absence of coverage at any one service level for a demand point is taken to imply lack of coverage in the grand measure of coverage. The problem's objective is the maximum coverage of population given specific limits on either the number of each type of facility or on the total investment that can be made in all facility types. Relaxed linear programming, supplemented by branch and bound where necessary, is used to solve the resulting integer programming problem. An application is described that uses distance and population data developed for a region of Honduras. Honduran nationals are currently being trained in the use of this and related location methodologies under a contract with the Agency for International Development. This effort is in support of work being undertaken by the Honduran National Planning Council to develop a nationwide data set of populated places in Honduras to which location methodologies will be applied.

This paper reports a real-life application of linear programming to corporate policy making. The model used in the study was designed to analyze the company's marketing and production policies. The model structure is unique, incorporating features of product mix, sequencing and blending models. The model's structure is described as well as typical results it produced. The recommendations for corporate actions arising from the model are also explained. Recommendations were made to alter the existing corporate policies on brand proliferation and limited inventory levels. The product line has been reduced as a result of the study, and a policy decision to expand the inventory has been made. The process of implementation is sketched to provide a feeling for the difficulties involved in corporate policy making.

This paper describes a simulation study of two cases of research and development planning. The first case is for a series of R&D projects analyzed sequentially by a single R&D team, while the second case is for a series of R&D projects analyzed sequentially and concurrently by two teams. Q-GERT, a network technique, was employed for the modeling and simulation effort. This technique includes numerous network modeling capabilities which make it more applicable to R&D project planning than traditional network techniques such as CPM and PERT. The simulation results for each case in terms of project duration statistics and outcome probabilities are presented in detail. The trade-offs between the two cases (i.e., single team versus multiple team analysis) are discussed.

This paper develops theoretical results, for a class of coordination mechanisms for resource allocation in decentralized firms, using as a model the decomposition of linear programs. Of the two pure decentralized allocation mechanisms (price-directive and resource-directive), resource-directive mechanisms, based in concept upon rationing or budgeting procedures, have received less attention in the literature. This paper focuses on these mechanisms and reports that under rather mild conditions the use of the plausible and economically appealing rule of allocating a global resource so as to equalize its marginal value over alternate uses is almost surely doomed to failure. In particular it is found that (1) resource-directive decompositions induce a kind of structural degeneracy in the decentralized divisions; (2) the amount of degeneracy increases with the number of divisions and the number of scarce global resources; and (3) degeneracy “seeks its own level” in that degeneracies spread over the divisions. The implication of these results for those interested in organizational design is that caution should be observed in utilizing such a rule as equalizing marginal values, and that more complicated and costly procedures for effecting resource allocation may be required. Finally, some symmetries between price-directive and resource-directive mechanisms are summarized.

This paper presents multi-criteria school busing models. More specifically, it reports on the application of goal programming to the school busing problem in order to achieve multiple, conflicting objectives. The models attempt to derive optimal solutions in order to reflect such goals as providing educational opportunity to children, striving for a racial balance, balancing overcrowding among schools, permitting the community school concept, and minimizing total transportation costs. The study offers practical applications of the approach to the complex social issue of busing.

This paper reports on a simulation study of multiple research and development projects that are worked on concurrently and sequentially by more than one research team. The technique employed in the modeling and simulation effort was GERT, which was used because of its capability to incorporate the probabilistic outcomes and feedback loops common to R&D projects. The GERT (Graphical Evaluation and Review Technique) includes the modeling of systems in network form and analysis through simulation. It is an important example of technological spin-off from space science research. GERT provides the capability to model and analyze networks of a very general form. Some of the features included in GERT networking are probabilistic branching (stochastic models), network looping (feedback loops), multiple sink nodes (multiple outcomes), multiple node realizations (repeat events), and multiple probability distributions (assigned to activity times). GERT networks are typically analyzed using the GERTS IIIZ simulation package, which provides statistics on project times and cost. Results of the simulation included statistical data on individual project duration and cost as well as overall network time and cost. These results were employed to provide management with an evaluation of different model configurations, prepare overall time and cost estimates as inputs to contract negotiations and to plan and schedule manpower, equipment and capital. Sensitivity analysts was employed to determine key stages in the R&D process where changes in success-failing probabilities might reduce network time and cost. Implementation experiences validated the model as satisfactory with the exception of several minor problems.