APPLICATION OF A PRODUCTIVITY MODEL FOR COMPUTER SYSTEMS*

The performance evaluation of computer systems as they impact on final user requirements for services is a complex task. A management-oriented approach to the issue based on conventional economic theory was described in a previous report as an outgrowth of a joint university-industry research project. In this sequel we report our experience in estimating, testing, and applying this conceptual model.     

AN ALTERNATE MODEL FOR LEAD-TIME DEMAND: CONTINUOUS-REVIEW INVENTORY SYSTEMS

The calculation of reorder points when the distribution of lead-time demand is normal is quite complex, primarily because of having to bound it away from negative demand values. A number of researchers have sought feasible alternative forms of lead-time demand which can be calculated without undue difficulty. It is proposed here to assume a Poisson (daily) demand and an exponential lead time (days). If they are assumed independent their convolution is geometric, which is itself asymptotically exponential. This has a number of advantages: (1) The exponential lead time is appropriate where the lead time is often short (i.e., local source), occasionally longer (when the local sources stock out), and, infrequently, quite long. (2) The geometric lead-time demand is independent of changes of time scale. (3) Reorder points and lot sizes appear in simple closed form. (4) The exponential asymptote is sufficiently close that this further simplification is usually warranted.     

MOTIVATION AND MANAGEMENT CONTROL SYSTEMS

The importance of motivation in the managerial control process has been well noted in the accounting literature. However, despite its emphasis on motivation, the accounting literature says little about the specific relationships between motivation and accounting control systems. This paper will present an explicit, systematic statement of these relationships by means of a detailed comparison and synthesis of two previously unrelated models. One is a conventional accounting model of control, and the other is a comprehensive behavioral model of motivation. Our aim is to integrate behavioral concepts with accounting applications in order to work towards solutions of important problems involving motivation and management control systems.     

A MODEL FOR OPTIMIZING FACILITY DESIGN

A chance constrained programming model is developed to arrive at an optimal long-range design for a manufacturing facility. The determination of process capacities, the amounts of the various types of equipment, and the time-phasing of the acquisition constitutes facility design in the study. The expected cost is minimised, subject to probabilistic constraints which express the risk associated with demand forecasts. The model is solved by decomposing the deterministic equivalent. The structure of the model enables the solution to be obtained with one iteration. The algorithm is incorporated into a computer code which is applied to the design of a tire plant. The methodology has the potential of extendability to nonmanufacturing systems.     

A DYNAMIC PROGRAMMING MODEL FOR PERIODICAL SELECTION

This paper presents a model for choosing the periodical collection in a reading room. The model consists of two stages. In the first stage the probability distribution of contacts by users with a given periodical is developed and employed to determine the utility of the periodical. In the second stage the problem of choosing an optimum periodical collection is formulated as a capital budgeting problem and solved with the aid of dynamic programming. The implementation of this model at the University of Connecticut is described in detail.     

A DECISION MODEL FOR SELECTING ALTERNATIVE HYPOTHESES

One important aspect of experimental design is the decision whether to use a one- or two-tailed hypothesis test. Assuming that the sample size and the level of significance have been specified, the selection of an alternative hypothesis can materially affect the conclusion drawn from the experiment. In the past, this selection was made on a subjective basis or for pragmatic reasons which can bias the experiment. This paper suggests an expected value approach, maximizing the expected power of the test, to place the selection of alternative hypotheses in an objective and reliable decision framework.     

A GOAL PROGRAMMING MODEL FOR OUTPUT PLANNING

This paper describes a goal programming procedure for determining satisfactory output plans for a work center. The situation being modeled is one in which work center inputs are known but vary significantly across time periods. Input levels are fixed relative to a given master production schedule, and output levels can be varied only within certain prescribed limits, at least in the short term. The similarity of the output planning problem to the more familiar aggregate planning problem is noted and discussed.     

THE ACADEMIC FLOW MODEL: A MARKOV-CHAIN MODEL FOR FACULTY PLANNING*

A Markov-chain faculty planning model to be used with institution-specific data is presented to describe and better understand the complex phenomena of faculty movement through an institution and on its relationship to salary costs, composition of the faculty, and faculty turnover rate. The model updates the earlier work done at Stanford University and Oregon State University by the addition of states for fixed-term appointments and for part-time FTEs to reflect accurately the current hiring trends at many institutions. The model is implemented and tested at two different institutions. The findings suggest that the model is a viable means of gaining useful insights and quantitative data on the faculty profile, salary costs, expected departures, and part-time trends. And further, when used as a planning tool, and the model apparently is comprehensive and flexible enough to analyze the probable effects, both in the short and long run, of alternative personnel policies on the faculty composition.     

THE APPLICATION OF A DYNAMIC FORECASTING MODEL WITH INVENTORY CONTROL PROPERTIES

This article summarizes the application of a forecasting model. Forecasts are made of monthly sales of products which do not change in style on an annual basis. The model is an exponential smoothing model. Adjustments of the parameters of the model are made whenever the average forecast error over the previous four periods is too large to be explained solely by unassignable causes. The efficiency gained in using the model is measured by the ratio of the standard deviation of the forecast errors to the standard deviation of sales. If this ratio is less than one, then the safety stock level that is carried for a given product can be reduced if sales are forecasted with the model and the standard deviation of the forecast errors is used to determine the safety stock level. The net effect is the reduction in the cost of carrying safety stocks. The results of the proposed model are also compared to a similar set of results generated from a basic, exponential model.     

META-DESIGN CONSIDERATIONS IN DEVELOPING MODEL MANAGEMENT SYSTEMS*

This paper examines cognitive considerations in developing model management systems (MMSs). First, two approaches to MMS design are reviewed briefly: one based on database theory and one based on knowledge-representation techniques. Then three major cognitive issues—human limitations, information storage and retrieval, and problem-solving strategies—and their implications for MMS design are discussed. Evidence indicates that automatic modeling, which generates more complicated models by integrating existing models automatically, is a critical function of model management systems. In order to discuss issues pertinent to automatic modeling, a graph-based framework for integrating models is introduced. The framework captures some aspects of the processes by which human beings develop models as route selections on a network of all possible alternatives. Based on this framework, three issues are investigated: (1) What are proper criteria for evaluating a model formulated by an MMS? (2) If more than one criterion is chosen for evaluation, how can evaluations on each of the criteria be combined to get an overall evaluation of the model? (3) When should a model be evaluated? Finally, examples are presented to illustrate various modeling strategies.     

A MATHEMATICAL PROGRAMMING MODEL FOR FACULTY COURSE ASSIGNMENTS

This paper describes an integer programming model that we believe has advantages over other models for determining faculty teaching assignments. Unlike previously proposed models, in this model the decision variables represent the assignment of complete teaching schedules rather than courses to faculty members. The paper compares the proposed model with previous models for application in an academic department.     

A GOAL PROGRAMMING MODEL FOR INSURANCE AGENCY MANAGEMENT

Rapid changes in the business environment have forced property and casualty insurance agencies to re-examine their objectives. The need to maintain contact with a large number of insurers in order to place business, efforts to reduce cost by utilizing company services, and the expanding demand for commercial lines have all had major impacts on these agencies. In this paper, a goal-programming model is developed for use in insurance agency decision-making involving multiple and often conflicting goals. An example is presented.     

A JOINT ECONOMIC-LOT-SIZE MODEL FOR PURCHASER AND VENDOR

In a typical purchasing situation, the issues of price, lot sizing, etc., usually are settled through negotiations between the purchaser and the vendor. Depending on the existing balance of power, the end result of such a bargaining process may be a near-optimal or optimal ordering policy for one of the parties (placing the other in a position of significant disadvantage) or, sometimes, inoptimal policies for both parties. This paper develops a joint economic-lot-size model for a special case where a vendor produces to order for a purchaser on a lot-for-lot basis under deterministic conditions. The focus of this model is the joint total relevant cost. It is shown that a jointly optimal ordering policy, together with an appropriate price adjustment, can be beneficial economically for both parties or, at the least, does not place either at a disadvantage.     

A PENSION DECISION MODEL FOR THE EMPLOYER*

Recently, the Financial Accounting Standards Board (FASB) reevaluated accounting for pension plans. The issue is emotional and highly political in nature. The FASB attempted to justify its approach on the basis of measuring economic activity, but it failed to provide much in the way of analytical support. This paper provides a managerial decision model and an economic basis for the existence of pension plans. A pension plan is described as a cost-saving, risk-sharing, incentive contract. The analysis is developed using agency theory. The model presented here meets three suggested objectives of an employer: 1. Maximization of utility through the maximization of profit 2. Ability to conform the risk characteristics of an employment contract to the risk characteristics of the employer 3. Diversification of the risk inherent in the employment contract Profit is maximized by producing cost savings associated with employee tenure and loyalty. Sharing cost savings with employees (i.e., offering a pension plan) meets the above objectives. The employer determines the optimal sharing rate for the expected cost savings. An examination of the employer's underlying decision process reveals implications for pension plan accounting which generally are consistent with and support the FASB's Statement of Financial Accounting Standards No. 87 [5].     

A DISCRETE-IN-TIME PROBABILISTIC INVENTORY MODEL FOR DETERIORATING ITEMS

A probabilistic scheduling-period inventory model continuous in units and discrete in time is developed for deteriorating items where deterioration is assumed to be a constant fraction of the on-hand inventory. The model is developed under the conditions of instantaneous delivery and no shortages. An example followed by sensitivity analysis is given to illustrate the derived results.     

A GENERAL APPROACH FOR COORDINATING PRODUCTION IN MULTIPLE-CELL MANUFACTURING SYSTEMS

We introduce a general approach to the coordination and control of material and information flow in multiple cell manufacturing systems. This approach uses production authorization cards (called PAC system) and generalizes such well-known approaches as MRP (material requirements planning), KANBAN (japanese card system), OPT (optimized production technology), BSS (base. stock system), IC (integral control), CONWIP (constant work-in-process), and others. It provides a framework for developing coordination and control mechanisms that combine the desirable features of more than one of these traditional approaches. The coordination is achieved by the rules that determine when and how material and information flow through the system and by the appropriate choice of the parameters of these rules. We also discuss various models of the PAC system that can be used to gain insight into the impact of the choices of the parameters. Directions for future research in this area is also outlined.     

A COMPARISON OF ALTERNATIVE FORECASTING STRATEGIES FOR MULTI-STAGE PRODUCTION-INVENTORY SYSTEMS

In multi-stage production-inventory systems, the demand for precursor items derives from the demand for successor items at the later stages in the system. This paper presents a method for evaluating the performance of two different strategies for forecasting the demand for precursor items. The dependent strategy relies on successor item forecasts to build a precursor item forecast, while the independent strategy relies on the extrapolation of past precursor demand. An expression indicating the conditions under which one strategy is preferred to the other is developed, and the effect of changing these conditions is illustrated with simulation results.     

EVALUATING MULTIPLE CRITERIA—MODELS FOR TWO-CRITERIA SITUATIONS

A general procedure is given for evaluating various alternatives (e.g., investments, projects, systems, etc.) involving two criteria of evaluation. The method involves the detailed questioning of decision makers as to preferences between various combinations of pre-selected sets of alternatives under various conditions. From the responses to such questions, a mathematical function which can be applied repeatedly for implementing choices between other alternatives is established. An example of the application of the procedure is given, along with discussion of certain ramifications of the example. In addition to the specific application, potential extensions of the technique are discussed briefly.