bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Efficiency of the Price, Budget, and Mixed Approaches Under Varying a Priori Information Levels for Decentralized Planning
Authors: Burton Richard M. , Obel Börge 
Published: November 2008

Organizations have a choice of information and planning procedures to use for a coordinated plan. In this paper, we investigate the efficacy of price and/or budget planning approaches, where the first proposal can be determined from a combination of historical plans, external prices, rules of thumb, and other data. The problem is to consider which planning approach and information structure are best. The experimental approach is to simulate the behavior of the planning approaches for a coordinated decentralized organization using decomposed mathematical programming models. The model is adapted from a Danish slaughterhouse. Many organizations use budgets and/or transfer prices to set coordinated plans. But optimization as defined mathematically is not a major concern. Organizations do consider a few alternative plans in an iterative process. We investigate the efficiency of the decomposition models as organizational analogues during the first five iterations to simulate organizational planning cycles. A changing environment for prices and availabilities is generated experimentally by perturbing these environmental parameters. A random number generator is used to yield the statistical sample. The experimental results are compared in terms of relative profitability for the organization. A nonparametric statistical test is used to analyze the experimental data. The results, are, in part, surprising. For a changing environment, historical information, (i.e., a past solution) is generally inferior to a combination of less precise information on current transfer prices, reasonable rules of thumb, and capacity constraints. However, more current information on prices and budgets yields better plans. Further, we found the transfer price approach yields more nearly optimal plans in the first few iterations than a combination of prices and budgets which in turn, is more efficient than budgets only.
Are Multi-Echelon Inventory Methods Worth Implementing in Systems with Low-Demand-Rate Items?
Authors: Muckstadt John A. , Thomas L. Joseph 
Published: November 2008

In practice, most multi-echelon inventory systems are managed using adaptations of single location methods. This paper shows that such methods can be dramatically inferior to methods designed to take advantage of a system's structure. This is especially true in repair parts inventory systems where most items have low demand rates. In this paper we describe a multi-echelon method adapted to a particular situation. Data taken from a large (over $100 million investment) industrial inventory system are used to provide comparative results on overall inventory required to meet a given service level. The multi-echelon method used involves an (s − 1, s) ordering policy and Poisson demand, both of which are appropriate for low demand items; this method requires much lower total investment than the single-location method requires to achieve the same average level of performance. Thus it appears that multi-echelon methods are worthwhile in many situations.
A Decision Analysis Model for a Serious Medical Problem
Authors: Peña Sanchez de Rivera Daniel 
Published: November 2008

This paper presents a decision model for a serious medical problem: the diagnosis and treatment of undifferentiated liver disease with jaundice. The model formalizes the use of information before a treatment is chosen, taking account of prior information collected by the doctor from laboratory and clinical exploration. Then the model chooses the best treatment according to the patient's preference structure. Since the best treatment in each case depends on the patient's preference for consequences, this aspect is central to the application of such models. Thus a main objective is to find a suitable criterion to measure the consequences in order that each patient's attitude can be taken into account. Our model was computerized and tested with fifty patients: the program duplicated in forty-four cases the decisions of expert doctors. The model overcomes some of the difficulties observed in the manipulation of probabilities by clinicians. The results suggest that a Decision Analysis model may be a useful way to clarify the decision process of expert clinicians and to help in the education of new doctors. Finally, this kind of program can play a role in automating medical decision-making in such a way that the knowledge of the best experts can be made widely available.
Note—Comments on a Queueing Inequality
Authors: Heyman Daniel P. 
Published: November 2008

In a G/G/c/N system (a queue with general distributions of inter-arrival and service time, c servers and N − c ≥ 0 queueing positions), let B be the steady-state probability that an arriving customer finds all queue positions filled and p be the time average probability that all queue positions are filled. By assuming p = B, Matthew Sobel proved [Formula: see text] where p is the traffic intensity. He also showed, by numerical examples, that the lower bound is a good approximation when p ≥ 1.5 and c ≥ 2. In this paper, we show that the lower bound does not require the assumption p = B to hold, and that it follows from the conservation of load. This derivation also explains why the bound does not depend on N and is a good approximation in heavy traffic. We also show that the upper bound depends critically on the assumption that p = B.
Note—Performance Evaluation of State-Owned Enterprises: A Process Perspective
Authors: Aharoni Yair 
Published: November 2008

State-Owned Enterprises (SOEs) have become important instruments of social and economic policy in industrialized mixed economies and in developing countries. The use of SOEs as instruments of public policy and the resulting clashes between these enterprises and private firms on the one hand and government and other controllers on the other, are causing concern. Public committees in different countries as well as international organizations have been searching for positive theory for guidance in handling the multitude of problems related to these enterprises. Theoretical models have made important contributions to the formalization of certain problems and the classification of the information needed to solve them. Unfortunately, these theoretical models have had little relevance for the solution of important real problems. Much of the research on SOEs is concerned with how these enterprises should behave, and what should be the product of their operations. Almost no research has been done on why SOEs function as they do. The paucity of knowledge about the operation of SOEs stems both from insufficient research effort, and from the concern of researchers with formal structures and products of these organizations and not with management behavior or with decision processes. The purpose of this paper is to call for research beyond the confines of traditional economics, using the tools of management science to obtain insights into the difficult but salient problems of SOEs.
Product-Mix Models When Learning Effects are Present
Authors: Reeves Gary R. , Sweigart James R. 
Published: November 2008

An important problem confronting decision makers in modern organizations is the determination of an optimal product-mix (or service-mix) in situations where learning effects are present. Learning has been observed to exist in a variety of production and service situations in which the amount of input required per unit of output decreases as total output increases. Little research has appeared, however, on the incorporation of learning effects into resource allocation models that attempt to determine good or optimal allocations of scarce resources to competing activities via mathematical programming. Enriching a traditional linear programming product-mix model to include learning effects results in a nonlinear model which may be more realistic, but is also likely to be more difficult to solve. In this paper, nonlinear product-mix models which incorporate learning effects are formulated and a procedure is developed for their solution. A key feature of the procedure is that decision makers are presented with good feasible solutions to a more realistic model early in the overall solution process together with bounds on the value of the best possible solution. Good feasible solutions and bounds are obtained with relatively little computational expense and effort through the use of linear approximation techniques. Feasible solutions serve as base points in a branch and bound process to refine solutions and bounds. Decision makers are able to terminate the solution procedure at any point prior to completion once a satisfactory, near optimal solution is identified. Alternatively, if allowed to run to completion, the solution procedure is capable of identifying and verifying a global optimal solution.
Minimizing Net Interest Cost in Municipal Bond Bidding
Authors: Nauss Robert M. , Keeler B. R. 
Published: November 2008

The problem of minimizing net interest cost (NIC) on new issues of tax-exempt debt securities is formulated as an integer linear programming problem. The formulation (for one variant) is a p-median problem with one additional constraint. Other variants are also closely related to the p-median problem. A dual ascent procedure for solving this problem class is presented and is incorporated in a branch and bound algorithm. Computational results are presented for a number of real world problems.
Methods of Large Project Assessment Given Uncertainty in Future Energy Pricing
Authors: Kalymon Basil A. 
Published: November 2008

The continuing oil crisis has created opportunities for developing sources of oil that had only been marginally economic previously. Many such projects, however, require large-scale investments that are recoverable only over very long lifetimes of operation. The profitability of such investments depends critically on the long-run pricing of oil in world markets and the interaction of the economic conditions of consuming nations. This paper develops a framework for analyzing the economics of such projects. Under the conventional assumption that appropriate levels of compensation for the required capital are needed before such large-scale projects are undertaken, the analysis focuses on the rate of return required to induce the large-scale capital expenditures. Both systematic and non-systematic risk exposure of such projects are identified and the critical linkage to world oil markets is defined through a simple market of world oil pricing. The understanding of the nature of project risks is critical to the development of government policy. The risk exposure of investors must be understood both for the development of risk reduction measures and for the establishment of suitable guidelines for capital compensation. The role of governments in energy investment has escalated and the implications for investments by the private sector require explicit recognition and study. It is shown that the traditional theory of risk pricing through the capital asset pricing model generally leads to conclusions that appear to be contradicted by observed investor behavior. Explanation and understanding of the nature of project risks incurred by the large-scale energy project must rely on more complex, disequilibrium models of risk determination. To illustrate the methodology developed, the paper considers investment in the Canadian tar-sands projects in Western Canada. A sensitivity analysis was performed on the rate of return of this project using simulation. The project was described in terms of both a world oil market and a taxation environment. For the range of conditions investigated, the rate of return was found to range between 4 and 20%, with a mean of 14.3% and a standard deviation of 3.3%.
A Mixed Integer Programming Model for Regional Planning of a Hospital Inpatient Service
Authors: Ruth R. Jean 
Published: November 2008

This paper describes a quantitative model to aid in planning an efficient and effective hospital inpatient service among hospitals in a region. The planning is to be done by a regional health systems planning agency, which sets or enforces standards of accessibility and acceptability to be achieved through a modification of the current system, particularly the allocation of beds to the population-at-risk. The allocation is defined in terms of matching beds to demand, where demand is classified by geographical areas and by level of care required. The allocation is to be done such that the planning goals, expressed in constraints on accessibility and acceptability of the inpatient service, are satisfied. In particular, the population within the region should have access to an adequate supply of beds, and the inpatient service should be of appropriate level and quality to meet the demand of the population. The planning problem is formulated as a mixed integer mathematical programming model in which changes to the system are described in terms of the location, number, conformance, and level of beds. There are two types of input to the model—estimates of demand by geographic area and level, and a description of the current state of the hospital service in the region. The current state of the hospital service is described by the location, size, level, and conformance of the service at existing hospitals and the location of possible new sites. The solution to the model is the lowest cost modification to the system that satisfies the constraints, where “cost” is a measure of the resources needed to change the system. Results from applying the model to the medical-surgical service in a region with 15 hospitals are discussed.
Variable-Base Budgeting for R&D
Authors: Blanning Robert W. 
Published: November 2008

An issue of theoretical and practical importance to R&D managers is the proper allocation of an organization's resources between the periodic selection and budgeting of R&D projects and the implementation of these projects. One possibility is to consider previous allocations as an established base and to restrict the attention of R&D managers to an examination of any subsequent deviations from the base. The advantage of this strategy, often called incremental budgeting, is that it focuses managerial and analytical efforts on a few current decisions. A second possibility, called zero-base budgeting, is to ignore previous allocations and to reexamine all feasible alternatives at the start of each budget cycle. This paper presents three models, a static model and two dynamic models, in which incremental and zero-base allocation procedures are viewed as extremes between which there may be a point of diminishing returns. The models are risk/return models in which a total budget is allocated between the budgeting effort, which reduces risk, and the budgeted activities, which increase expected return. The budget for each activity during each time stage is partitioned into two components—a base and an increment. The expected return for each activity is a concave increasing function of its budget, and the risk depends quadratically on the base and in a geometrically decreasing fashion, on the bases in previous stages. The cost of evaluation is proportional to the increment, and the total cost of all activities, when added to the budgets for the activities, cannot exceed a fixed total budget. Zero-base budgeting means setting the base to zero so that the budget equals the increment plus the cost of evaluation. It is shown that a policy of zero-base budgeting during all time stages is nonoptimal, but an instance of zero-base budgeting during a single stage may be optimal.
An Experimental Investigation of the Use of Computer-Based Graphics in Decision Making
Authors: Lucas Henry C. 
Published: November 2008

This paper presents the results of an experiment designed to investigate the impact of computer-based graphics on decision making. The experimental task consisted of selecting quarterly reorder quantities for an importer under condition of uncertain demand. Subjects in the experiment were participants in an executive program for middle and upper level managers. Each subject received information on the cumulative probability distribution of demand and had an opportunity to run up to eight trial simulations with past demand data using his or her order quantities. After completing the trial simulations, the subjects made quarterly ordering decisions for one year in which the quantities demanded were drawn from the demand distribution. Treatments included the use of a hard copy terminal and five different types of displays on a CRT. The results of the experiment provide limited support for the use of graphics presentation in an information system. Decision or cognitive style also appears to be an important variable influencing the performance of an individual and the reaction to an information system. The implications of the findings for the design of information systems are discussed.
Project Scheduling with Continuously-Divisible, Doubly Constrained Resources
Authors: Węglarz Jan 
Published: November 2008

This paper deals with a class of project scheduling problems concerning the allocation of continuously divisible resources under conditions in which both total usage at every moment and total consumption over the period of project duration are constrained. Typical examples of such resources, called doubly constrained, are money or energy, when the constraint on power or the rate of expenditure cannot be ignored as neither, of course, can. the constraint on resource consumption. Also manpower must often be considered as a doubly constrained resource. Mathematical models of project activities in which performing speeds are continuous functions of resource amounts are considered. The objective is a schedule which minimizes project duration. Thus, the problems considered are generalizations of both the classical project scheduling problem and the time-cost trade-off problem. The properties of optimal schedules are given for strictly concave, concave and convex activity models. On the basis of these properties, methods for finding optimal schedules are described for independent and dependent activities. We also consider the minimum resource consumption ensuring minimum project duration for a given level of resource usage, and the minimum level of resource usage ensuring minimum project duration for a given level of resource consumption. Possible generalizations of the presented results are indicated.
An Application of Mathematical Programming to Assess Productivity in the Houston Independent School District
Authors: Bessent A. , Bessent W. , Kennington J. , Reagan B. 
Published: November 2008

A school may be viewed as an enterprise in which the professional staff provide the operating conditions for converting quantifiable resources or inputs into pupil learning (outputs). The resources are determined by budgets, teacher assignments, and student assignments while learning is determined by various outputs scored according to standardized tests such as the Iowa Test of Basic Skills. Following the work of Charnes, Cooper, and Rhodes (Charnes, A., W. W. Cooper, E. Rhodes. 1981. Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through. Management Sci. 27 (6) 668–697.), we use a ratio definition of efficiency that takes account of all outputs and inputs without requiring a priori specification of weights. Instead a series of mathematical programs are applied to determine “virtual multipliers” from actual data. The multipliers produce values that can be regarded as the “most favorable weights” for each school being evaluated. If the resulting optimum virtual multipliers for a given school yield an efficiency ratio of one, then that school is said to be efficient. If the ratio is less than one then that school is said to be inefficient relative to the other schools in the analysis. The ratio is also accorded operational significance—it is not merely an index number—so that the resulting values and the associated virtual multipliers make it possible to locate where improvements may be made along with their relative magnitudes. This analysis was applied to 167 elementary schools in the Houston Independent School District. Of these schools, 78 were found to be inefficiently utilizing their resources as compared to the 89 efficient schools. Based on this pilot study, an Educational Productivity Council has been formed at the University of Texas at Austin to provide an annual analysis for all of its member schools. At present 285 Texas schools in 22 districts are scheduled for participation in the annual analysis as described in this investigation.
Multiperiod Resource Allocation with Variable Technology
Authors: Reeves Gary R. , Sweigart James R. 
Published: November 2008

Planning the allocation of scarce resources to competing activities over multiple time periods is one of the most important problems facing decision makers in modern organizations. Much of the previous research in this area has concentrated on the use of linear programming procedures and has assumed that the technology through which scarce resource inputs are transformed into competing activity outputs is fixed. A more realistic assumption in many situations is that certain technology coefficients are likely to vary over the planning horizon as a function of activity levels in previous periods. In this paper, a multiperiod resource allocation model with variable technology is formulated. Enriching a more traditional fixed technology model to include variable technology results in a nonlinear model which is more realistic, but is also more difficult to solve. A heuristic procedure that is both straightforward and intuitively appealing is developed for obtaining good feasible solutions to the variable technology model. The solution procedure requires little additional computational effort beyond solving the associated, less realistic fixed technology model.
Toward Valid Measures of Public Sector Productivity: Performance Measures in Urban Transit
Authors: Gleason John M. , Barnum Darold T. 
Published: November 2008

In recent years, performance measurement has become the focus of attention in a variety of public sector fields. Unfortunately, too little has been done to develop valid operational definitions of performance, or to identify the weaknesses and biases inherent m certain types of performance measures. Thus, the potential exists for the inappropriate use of certain indicators in performance evaluations and decisions. One field in which there has been increasing effort to deal with performance problems is that of transit. Regardless, the nebulous nature of “performance” has been all too apparent in this industry. The terms “productivity,” “efficiency,” and “effectiveness” have been used synonymously in some instances, while in other cases “efficiency” and “effectiveness” have been considered to be different aspects of overall “productivity.” This confusion is of major significance, because the use of performance measures in operations assessment, decision making, and resource allocation is increasing. Furthermore, since it increasingly is being urged that subsidy payments be linked to the performance of a transit system, and since subsidies now constitute over half of transit revenues, the performance measurement problem is particularly important. This paper examines weaknesses and biases inherent in commonly used measures of urban mass transit performance. It is shown that measures of efficiency, such as cost per passenger, are being incorrectly used as measures of effectiveness and that various traditional measures of efficiency, such as those which incorporate mileage, can be misleading when applied in decision making. Suggestions are made for developing valid performance indicators and for developing safeguards that will avoid present shortcomings.