bluuebunny/crossref_metadata_2025 huggingface dataset:
A MATHEMATICAL PROGRAMMING MODEL FOR FACULTY COURSE ASSIGNMENTS
Authors: McClure Richard H. , Wells Charles E.
Published: June 2007

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.
DEVIL'S ADVOCACY AND DIALECTICAL INQUIRY EFFECTS ON PREDICTION PERFORMANCE: TASK INVOLVEMENT AS A MEDIATING VARIABLE
Authors: Schwenk Charles R.
Published: June 2007

Critics of previous laboratory experiments comparing devil's advocacy (DA) to dialectical inquiry (DI) have suggested that these experiments produced misleading results because (1) they used subjects who had low levels of task involvement and (2) the DI treatment used was confusing to subjects and required further explanation to be useful. The present study examines the effects of four inquiry methods—expert (E), DA, DI, and DI with explanatory statement (DI+)—on subjects' performance at a financial prediction task. Results show that DA, DI, and DI + were superior to E when the state of the world differed significantly from assumptions underlying the expert's plan. For subjects with high task involvement, DI and DI + were more effective than E and DA. The results support some of the criticisms of previous laboratory research and suggest that future research on these decision aids should include task involvement as a factor.
TALKING ABOUT PROBABILITIES: A LOGICAL PROBLEM FOR OR/MS
Authors: Singer Alan , Davies John , Huang Ming S.
Published: June 2007

The correct interpretation of a natural language statement is determined as much by convention and shared meanings as by logical content. Therefore, when the word “probability” is used in the statement of a decision problem, the intended interpretation is not always clear. If such a statement also contains explicit probability formulae, confusion and even paradox may result. In this article, a problem involving cascaded inference is interpreted in four ways, three of which are regarded by the authors as legitimate or reasonable. The problem was originally suggested by Einhorn [3] and further discussed by Libby [10]. It is suggested here that a formal, mathematicist interpretation of the word “probability” might lead to inappropriate analyses of some decisions.
SOME STATISTICAL ISSUES IN THE ESTIMATION OF A SIMPLE COST‐VOLUME‐PROFIT MODEL*
Authors: Cantrell R. Stephen , Ramsay Louis P.
Published: June 2007

This paper presents point and interval estimators of both long‐run and single‐period target quantities in a simple cost‐volume‐profit (C‐V‐P) model. This model is a stochastic version of the “accountant's break‐even chart” where the major component is a semivariable cost function. Although these features suggest obvious possibilities for practical application, a major purpose of this paper is to examine the statistical properties of target quantity estimators in C‐V‐P analysis. It is shown that point estimators of target quantity are biased and possess no moments of positive order, but are consistent. These properties are also shared by previous break‐even models, even when all parameters are assumed known with certainty. After a test for positive variable margins, Fieller's [6] method is used to obtain interval estimators of relevant target quantities. This procedure therefore minimizes possible ambiguities in stochastic break‐even analysis (noted by Ekern [3]).
Concepts, Theory, and Techniques ON THE USE OF THE GEOMETRIC MEAN IN LONG‐TERM INVESTMENT
Authors: Cheng David C. , Karson Marvin J.
Published: June 2007

Application of the geometric mean to holding‐period returns is discussed from a statistical theory standpoint. The population geometric mean is considered a parameter of the probability distribution of returns its relationship to moments of the distribution is discussed. The sample geometric mean and its relation to sample moments is assessed through its sampling distribution it is viewed as an estimator of the population geometric mean. For application to long‐term investment where a geometric mean is maximized, the distributional properties of the geometric mean should be used. The terms statistic, approximation, and parameter are differentiated.
A DISCRETE DYNAMIC OPTIMIZATION MODEL FOR MADE‐TO‐ORDER COST ANALYSIS
Authors: Gulledge Thomas R. , Womer Norman Keith , Tarimcilar M. Murat
Published: June 2007

A model is presented that yields optimal production rates for a firm producing a contracted order. The model is unique in that it considers the influence of production rate and learning on total program cost. An application to the specific characteristics of two military production programs is presented. As demonstrated by the application, models of this type may be used as decision‐making tools when negotiating the cost impact of contract modifications.
Applications and Implementation DATA‐BASE MANAGEMENT SYSTEM EVALUATION AND SELECTION DECISIONS*
Authors: Zahedi Fatemeh
Published: June 2007

The rapid increase in the use of data‐base management systems (DBMSs) has created a need for structured methods of evaluation and selection. This paper offers one such method. It develops a decision schema for data‐base software selection that is data‐model independent and contains structural associations. A decision analysis method, the analytic hierarchy process (AHP), is used to quantify the evaluation. The method developed in this paper is applied to the evaluation of two microcomputer DBMS products: dBASE II® and Condor 3®.
Concepts, Theory, and Techniques PRINCIPLES OF MULTIOBJECTIVE OPTIMIZATION*
Authors: Rosenthal Richard E.
Published: June 2007

This paper attempts to isolate and analyze the principal ideas of multiobjective optimization. We do this without casting aspersions on single‐objective optimization or championing any one multiobjective technique. We examine each fundamental idea for strengths and weaknesses and subject two—efficiency and utility—to extended consideration. Some general recommendations are made in light of this analysis. Besides the simple advice to retain single‐objective optimization as a possible approach, we suggest that three broad classes of multiobjective techniques are very promising in terms of reliably, and believably, achieving a most preferred solution. These are: (1) partial generation of the efficient set, a rubric we use to unify a wide spectrum of both interactive and analytic methods; (2) explicit utility maximization, a much‐overlooked approach combining multiattribute decision theory and mathematical programming; and (3) interactive implicit utility maximization, the popular class of methods introduced by Geoffrion, Dyer, and Feinberg [24] and extended significantly by others.
ACCURACY OF JUDGMENTAL FORECASTING OF TIME SERIES
Authors: Carbone Robert , Gorr Wilpen L.
Published: June 2007

Experiments contrasted judgmental and objective forecast methods. Judgmental methods included “eyeball” extrapolation of time‐series plots and judgmental adjustment. Objective methods included Box‐Jenkins (BJ), Carbone‐Longini AEP filtering (CL), Holt‐Winters (HW), and other smoothing techniques. Objective methods proved more accurate than eyeball extrapolation. However, judgmental adjustment improved the accuracy of some objective forecasts.
FORECAST EVALUATION OF LIVINGSTON DATA ON INFLATION RATES AND INFLATION UNCERTAINTY*
Authors: Cargili Thomas F. , Meyer Robert A.
Published: June 2007

Livingston data on expected inflation rates have been used extensively in the financial literature, especially in investgating the relationship between nominal interest rates and expected inflation rates; however, the data have not been subjected to a thorough analysis of forecast accuracy. The objective of this paper is to analyze the forecast properties of Livingston data using a wide variety of time and frequency domain methods over an extended sample period and for selected subperiods.
AN EVALUATION OF SEQUENCING RULES FOR AN ASSEMBLY SHOP
Authors: Russell Roberta S. , Taylor Bernard W.
Published: June 2007

Research relating to sequencing rules in simple job shops has proliferated, but there has not been a corresponding proliferation of research evaluating similar sequencing rules in more complex assembly job shops. In a simple job shop, all operations are performed serially; but an assembly shop encompasses both serial and parallel operations. As a result of the increased complexity of assembly shops, the results associated with the performance of sequencing rules in simple job shops cannot be expected for an assembly shop. In this paper, 11 sequencing rules (some of which are common to simple job shops and some decigned specifically for assembly shops) are evaluated using a simulation analysis of a hypothetical assembly shop. The simulation results are analyzed using an ANOVA procedure that identifies significant differences in the results of several performance measures. Sensitivity analysis also is performed to determine the effect of job structure on the performance of the sequencing rules.
Concepts, Theory, and Techniques ROBUST METHODS: AN ALTERNATIVE APPROACH FOR ANALYZING DATA SETS CONTAINING INFLUENTIAL DATA POINTS
Authors: Chatterjee Sangit , Wiseman Frederick
Published: June 2007

Recent advances in statistical estimation theory have resulted in the development of new procedures, called robust methods, that can be used to estimate the coefficients of a regression model. Because such methods take into account the impact of discrepant data points during the initial estimation process, they offer a number of advantages over ordinary least squares and other analytical procedures (such as the analysis of outliers or regression diagnostics).

This paper describes the robust method of analysis and illustrates its potential usefulness by applying the technique to two data sets. The first application uses artificial data; the second uses a data set analyzed previously by Tufte [15] and, more recently, by Chatterjee and Wiseman [6].
ROBUST METHODS APPLIED TO ENERGY‐CONSUMPTION DATA
Authors: Janson Marius A. , Willis Raymond E.
Published: June 2007

In many instances a model is based on nonexperimental data and is used for prediction. In this situation, using both the least‐squares and the robust methods simultaneously can result in models with improved predictive performance.
NEW TECHNOLOGY INVESTMENTS IN MULTISTAGE PRODUCTION SYSTEMS
Authors: Chakravarty Amiya K. , Shtub Avraham
Published: June 2007

The introduction of new technologies in production and manufacturing (such as robotics, flexible manufacturing systems (FMS), and computer‐aided design and manufacturing (CAD/CAM)) frequently motivates capital investment decisions. Traditionally, the need for additional capacity has motivated the evaluation of investment decisions which were undertaken based on financial factors such as the net present value (NPV), internal rate of return, taxation, and depreciation.

This research integrates investment decisions with operational decisions for the case of multistage production assembly systems. We show that for such systems investment decisions affect not only the financial structure but also production scheduling and material flow in the system.
AN EMPIRICAL VALIDATION OF ADAM IN A CAPITAL BUDGETING CONTEXT*
Authors: Bao Da‐Hsien
Published: June 2007

The attribute‐dynamic attitude model (ADAM) offers a description of decision processes that has greater theoretical appeal than that offered by the multiple regression model. It distinguishes judgment from choice, explains inconsistent behavior, and shows the implications of criterion weight modifications when decision situations change. This study tests the validity of ADAM empirically in a capital budgeting context. Results of a laboratory experiment show that: (1) ADAM is a good ex ante descriptor of decision processes and (2) ADAM weights are context dependent and differ significantly from a priori weights. The results support an equal‐weighting theory.
THE IMPACT OF EXTREME OBSERVATIONS ON SIMPLE FORECASTING METHODS*
Authors: Kucukemiroglu Orsay , Ord Keith
Published: June 2007

In general linear modeling, an alternative to the method of least squares (LS) is the least absolute deviations (LAD) procedure. Although LS is more widely used, the LAD approach yields better estimates in the presence of outliers. In this paper, we examine the performance of LAD estimators for the parameters of the first‐order autoregressive model in the presence of outliers. A simulation study compared these estimates with those given by LS. The general conclusion is that LAD does not deal successfully with additive outliers. A simple procedure is proposed which allows exception reporting when outliers occur.
Concepts, Theory, and Techniques A JOINT LOT‐SIZING RULE FOR FIXED LABOR‐COST SITUATIONS
Authors: Pinto Peter A. , Mabert Vincent A.
Published: June 2007

Many American firms are implementing just‐in‐time production in order to minimize inventories, reduce flow time, and maximize resource utilization. These firms recognize that, in the short run, setup costs really are fixed expenses and it is available capacity which is the critical factor in determining production‐run quantities. We propose using available capacity to increase the number of setups and reduce lot‐size inventories. This results in improved relevant cost performance. Sugimori, Kusunoki, Cho, and Uchikawa [16] in their paper on the Toyota kanban system developed a relationship for lead time but failed to use it for lot sizing. We use this relationship to develop the joint lot‐sizing rule. The efficacy of our proposed rule is demonstrated by applying it to lot‐size scheduling problems at the John Deere Engine Works [14]. Extensions of the proposed rule to undercapacity situations with material‐wastage costs in the setup processes and to multistate production inventory systems also are discussed.
COMPARISON OF CONSENSUS METHODS FOR PRIORITY RANKING PROBLEMS
Authors: Jensen Robert E.
Published: June 2007

Various consensus methods proposed for ranking problems yield controversial rankings and/or tied rankings which are vulnerable to considerable dispute. These include Borda‐Kendall (BK) and minimum‐variance (MV) methods. This paper compares three continuous (ratio‐scale) consensus scoring methods with BK and MV ranking methods. One method, termed GM, is an eigenvector scaling of the geometric‐mean consensus matrix. GM allows for (1) paired‐comparison voting inputs (as opposed to all‐at‐once ranking), (2) pick‐the‐winner preference voting, and (3) ratio‐scale preference voting. GM is relatively simple to calculate on small computers or calculators, and merging of “close” candidates into tied rankings can be achieved by using an e‐threshold tie rule discussed in this paper. The GM method thus can be used for paired‐comparison voting to calculate both a ratio‐scaled consensus index (based on a consensus eigenvector) and a ranking of candidates that allows for ties between “close” candidates. Eigenvalue analysis is used as a means of evaluating voter inconsistencies.
ON TWO‐SOURCE FACTOR PURCHASING
Authors: Horowitz Ira
Published: June 2007

Two‐source purchasing at differing factor‐unit costs is a common real‐world phenomenon. So too are uncertainty and risk aversion which, as this paper demonstrates, provides one explanation for why firms on occasion purchase from high‐cost sellers.
OPTIMAL SAFETY‐STOCK INVESTMENT THROUGH SUBJECTIVE EVALUATION OF STOCKOUT COSTS
Authors: Badinelli Ralph D.
Published: June 2007

This paper solves the problem of setting safety stocks by combining a subjective evaluation of the stockout‐cost function with the usual holding‐cost function. The technique given in this paper for estimating a decision maker's (DM's) disvalue function for stockouts is robust in terms of the shapes permissible for this function and allows for uncertainty on the part of the DM in expressing his/her trade‐offs. The estimation technique could be applied to situations other than the safety‐stock problem. We provide an optimization routine for the safety‐stock problem which is designed to operate in conjunction with the estimation technique. Safety‐stock levels are arrived at iteratively.
MODELS OF PARTS‐ORIENTING SYSTEMS*
Authors: Yeralan Sencer , Chang C. Alec
Published: June 2007

An analytical model to estimate, evaluate, and compare the behavior and performance of parts‐orienting systems for automated manufacturing systems is developed. The model can be applied to parts‐orienting systems for both traditional series‐structured manufacturing systems and nontraditionally structured flexible manufacturing systems. Numerical examples are given for typical system configurations such as the pure series system, the pure parallel system, and the pure feedback system.
Concepts, Theory, and Techniques DISTRIBUTED COMPUTER SYSTEM DESIGN: A MULTICRITERIA DECISION‐MAKING METHODOLOGY*
Authors: Jain Hemant K. , Dutta Amitava
Published: June 2007

The design of distributed computer systems (DCSs) requires compromise among several conflicting objectives. For instance, high system availability conflicts with low cost which in turn conflicts with quick response time. This paper presents an approach, based on multi‐criteria decision‐making techniques, to arrive at a good design in this multiobjective environment. An interactive procedure is developed to support the decision making of system designers. Starting from an initial solution, the procedure presents a sequence of non‐dominated vectors to designers, allowing them to explore systematically alternative possibilities on the path to a final design. The model user has control over trade‐offs among different design objectives. This paper focuses on the details of the mathematical model used to provide decision support. Accordingly, a formulation of DCS design as a multicriteria decision problem is developed. The exchange search heuristic used to generate nondominated solutions also is presented. We argue that multicriteria models provide a more realistic formulation of the DCS design problem than the single‐criterion models used widely in the literature. While obtaining a clear definition of design objectives (single or multiple) is an important activity, by explicitly acknowledging the trade‐offs among multiple objectives in the design process, our methodology is more likely to produce a better overall design than methods addressing a single criterion in isolation.
ENVIRONMENTAL VOLATILITY, SYSTEM ADAPTATION, PLANNING REQUIREMENTS, AND INFORMATION‐PROCESSING STRATEGIES: AN INTEGRATIVE MODEL
Authors: Hartman Sandra J. , White Michael C. , Crino Michael D.
Published: June 2007

As noted in the literature, comparatively little research has examined either descriptive or prescriptive modeling of the planning process. A major reason for this lack of research appears to be the difficulty of comparing and testing planning methods within and across actual organizations. The purpose of this paper is to present a prescriptive planning model based on information‐processing research and strategies. This model explicitly considers the linkages among the environment, the organization's adaptation to that environment, the type of planning, and information‐processing strategies.
Applications and Implementation A MANAGEMENT SYSTEMS ANALYSIS OF THE ARMS TRANSFER PROCESS*
Authors: Clark Thomas D.
Published: June 2007

The decision and information structure of the arms transfer process from major powers (especially the United States) to third‐world countries is discussed. System behavior as a result of system structure, political forces, and economic factors is the focus of analysis. A system‐dynamics model of transfer structures is developed and discussed. Examples of policy alternatives in arms transfer are illustrated and discussed.
A PENSION DECISION MODEL FOR THE EMPLOYER*
Authors: Mielke David E.
Published: June 2007

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].
Notes and Communications RESOLVING CERTAIN DIFFICULTIES AND IMPROVING THE CLASSIFICATION POWER OF LP DISCRIMINANT ANALYSIS FORMULATIONS
Authors: Freed Ned , Glover Fred
Published: June 2007

In certain settings, difficulties arise that limit the effectiveness of LP formulations for the discriminant problem. Explanations and possible remedies have been offered, but these have had only limited success. We provide a simple way to overcome these problems based on an appropriate use and interpretation of normalizations. In addition, we demonstrate a normalization that is invariant under all translations of the problem data, providing a stability property not shared by previous approaches. Finally, we discuss the possibility of using more general models to improve discrimination.
A COMPARISON OF UNIT, SUBJECTIVE, AND REGRESSION MEASURES OF SECOND‐LEVEL VALENCES IN EXPECTANCY THEORY
Authors: Stahl Michael J. , Grigsby David W.
Published: June 2007

Two different decision‐making exercises are compared with unit weights and with traditional Likert scales as measures of second‐level valences in expectancy theory. Second‐level valences are measured across different levels of outcomes in each exercise and compared to the traditional subjective‐ and unit‐weight measures. In the first experiment, the job‐preference decisions of 21 undergraduates are examined using a decision‐making exercise involving 24 hypothetical jobs described in terms of three intrinsic instrumentalities at two levels. In the second experiment, a different 21 undergraduates make job‐preference decisions in a decision‐making exercise involving 27 hypothetical jobs described in terms of three extrinsic instrumentalities at three levels. The β‐weight (standardized regression coefficient) measures of the second‐level valences are found to be more powerful predictors of job‐preference decisions than either subjective‐weight or unit‐weight measures, both before and after shrinkage. They also had higher cross validations, exhibited higher test‐retest reliability, and allowed testing of a quadratic motivational effect in the three‐level exercise.
AN ECONOMIC MODELING APPROACH FOR THE DETERMINATION OF MATERIALITY IN AUDITING
Authors: Crosby Michael , Plante Robert , Tang Kwei
Published: June 2007

The concept of materiality pervades the audit process. Typically, materiality is determined as a percentage of the total book value of an account or as a percentage of net income. We propose an economically based model that determines that materiality level which minimizes the economic consequences of the audit decision. The proposed model is examined for materiality sensitivity to prior information concerning the quality of the accounting process and to costs incurred as a consequence of the audit decision.
THE TAX LITIGATION DECISION: AN ANALYSIS OF THE SMALL CLAIMS DIVISION OF THE U.S. TAX COURT*
Authors: Curatola Anthony P. , Fields Kent T. , Ringuest Jeffrey L. , Samson William D.
Published: June 2007

One of the more difficult but intriguing problems in the tax field is the decision of when (and how) to settle tax disputes with the Internal Revenue Service (IRS) and when (and how) to litigate. Research in this area of decision making is limited and has concentrated on the probability of winning in the judicial system. This paper examines the tax litigation decision for suits in the Small Claims Division of the U.S. Tax Court. Four examples are presented which involve varying degrees of information regarding the likelihood of a settlement and differing risk attitudes. The maximum amount the taxpayer should be willing to spend in pursuing litigation is derived for each case.
THE INTERACTION BETWEEN THE RELATIVE ACCURACY OF PROBABILISTIC VS. DETERMINISTIC PREDICTIONS AND THE LEVEL OF PREDICTION‐TASK DIFFICULTY*
Authors: Eckel Norm
Published: June 2007

An experimental paradigm was constructed to assess the impact of prediction‐task difficulty on the relative accuracy of probabilistic versus deterministic predictions. The results strongly support the hypothesis that the accuracy of probabilistic versus deterministic predictions is related to the level of difficulty inherent in the prediction task. At low levels of prediction‐task difficulty, deterministic predictions were mort accurate than probabilistic predictions; the converse was true at high levels of difficulty.
PROCEDURES FOR DETERMINING RELATIVE FREQUENCIES OF PRODUCTION/ORDER IN MULTISTAGE ASSEMBLY SYSTEMS*
Authors: Moily Jaya P. , Matthews John P.
Published: June 2007

We show that the problems of determination lot sizes in a multistage assembly system for the case of instantaneous production and constant demand for the end item can be reduced to the problems of determining relative frequenceis of production/order for items at each production stage. We further show that such frequencies are independent of the demand levels. Optimal and near‐optimal solution procedures for this reduced problem are provided. The near‐optimal procedure successively treats each stage of production as a final production stage while simulatenously incorporating decisions made at lower stages into decisions made at higher stages. Experimental results show that the near‐optimal procedure results in optimal solutions 75 percent of the time and performs considerably better than representative heuristics available in the literature. Further, its performance is relatively less susceptible to product/structural characteristics of the system.
A PREFORMANCE ANALYSIS OF PARAMETRIC AND NONPARAMETRIC DISCRIMINANT APPROACHES TO BUSINESS DECISION MAKING
Authors: Mahmood Mo. A. , Lawrence Edwared C.
Published: June 2007

This paper empirically investigation the performance of four relatively new nonparametric techniques against four different parameteric versions of discriminant analysis. The models were constructed and analyzed using financial data drawn from 232 bankrupt and nonbankrupt companies. Generally, the nonparametric approaches, with the exception of linear programming, performed as well as or better than the more traditional discriminant analysis.
RATIONING DISCRETIONARY ECONOMIC RESOURCES: A MULTIOBJECTIVE APPROACH
Authors: Nunamaker Thomas R. , Truitt Jack F.
Published: June 2007

Prior research involving capital rationing has focused on capital budgeting issues: given a limited resource pool, which major long‐lived fixed assets should be acquired? However, capital rationing can be extended to include not only new fixed‐asset purchases but also expenditures for any other discretionary activity such as advertising, research and development, or maintenance. In this broader situation, measuring the contributions of certain discretionary activities to a single objective (e.g., maximize profits) or to multiple objectives often is hindered by a lack of reliable revenue estimates. This problem severely hampers the usefulness of traditional mathematical programming approaches to capital rationing. In this paper, we modify the usual multiobjective capital rationing procedures by treating each discretionary activity as an objective in itself. In this manner, we can mitigate the difficulties associated with revenue measurement problems and allow a decision maker systematically to explore the various trade‐offs between competing discretionary investments.
PARTICIPATION IN BUDGETARY DECISION MAKING, TASK DIFFICULTY, LOCUS OF CONTROL, AND EMPLOYEE BEHAVIOR: AN EMPIRICAL STUDY*
Authors: Mia Lokman
Published: June 2007

This study investigates the relationship between participation in budgetary decision making and attitude (toward job and employer), taking into account the effects of task difficulty and locus of control on participation and attitude. Managers from two companies participated in the study. Attitude was found to be related positively to participation and negatively to task difficulty. Implications of the results are discusses.
A DISCRETE PRODUCTION SWITCHING RULE FOR AGGREGATE PLANNING
Authors: Oliff Michael D. , Leong G. Keong
Published: June 2007

Aggregate planning (AP) is a necessary activity for manufacturing and services alike. A shift toward high‐volume batch and continuous flow processes within American manufacturing has given rise to increasing numbers of crew‐loaded facilities. A majority of AP approaches incorporate continuous decision variables and require frequent adjustments to both production and work‐force settings. Despite the availability and diversity of these approaches, few significant applications have been reported. This paper presents the detailed development of a discrete AP switching rule that can be applied to a variety of cost environments. Inventory costs are estimated using an interval approach rather than traditional point estimates. The model allows incorporation of overtime options and is interactive in nature. Decision variables from the model can be disaggregated and linked directly to lower‐level planning activities. Actual results of model implementation are reported. An overview of the model's incorporation into the larger context of hierarchical production planning is found in [21].
A NOTE ON AN APPLICATION OF THE ANALYTIC HIERARCHY PROCESS
Authors: Wu Nesa L'abbe
Published: June 2007

This note is a response to an article by Zahedi [2] published in the Winter 1985 issue of Decision Sciences. It demonstrates that there is no need to calculate eigenvalues for consistent pairwise comparison matrices in order to calculate normalized values of attributes.
MATHEMATICAL FORMULATION OF THE TASK SEGREGATION PROBLEM IN INTERNAL CONTROL SYSTEM DESIGN*
Authors: Srinidhi Bin N.
Published: June 2007

Segregation of tasks is an important factor in the determination of internal control system reliability. In assigning tasks within an organization, the impact on internal control system reliability must be considered. This paper uses reliability modeling as the basis of a method for formulating the design problem. Formulation of the problem in this manner facilitates development of a knowledge base for auditors' judgments and the use of such knowledge in the design problem. It is demonstrated that under certain conditions the problem can be solved easily. This is useful not only in task assignment but also in manpower decisions. New concepts such as reliability degradation and a task combination matrix are introduced in developing the formulation.
AFFECTIVE RESPONSES WITHIN A COMPLEX DECISION‐MAKING TASK: THE INFLUENCE OF “PERCEPTUALLY” ILL‐STRUCTURED PROBLEMS
Authors: III Taylor Lewis A.
Published: June 2007

The perceptual effects of varying levels of expert advice for potentially improving on strategic decisions were examined in conjunction with goals. The amounts of advice about decision alternatives, as well as assigned goals ranging from “nearly impossible” to “easy,” were manipulated. The task used was complex and functioned perceptually as an “ill‐structured” problem. Mixed results indicated that more advice significantly affected satisfaction but advice in general had little influence on effort. On the other hand, as goal difficulty decreased, satisfaction and effort significantly increased. Easy goals were superior to more difficult ones within this perceptually ill‐structured decision‐making situation.
USING CONJOINT ANALYSIS TO PREDICT TRIAL AND REPEAT‐PURCHASE PATTERNS OF NEW FREQUENTLY PURCHASED PRODUCTS*
Authors: Zufryden Fred S.
Published: June 2007

A new approach is proposed to evaluate new‐product opportunities. This approach uses the distribution of brand‐purchase probability of the new product over a population of potential customers and the outputs from conjoint analysis. The heterogeneous distribution of brand‐purchase probability is expressed by a beta binomial brand‐choice model compounded with a negative binomial product‐class purchase‐incidence model. The resulting model provides a way to predict trial and repeat‐purchase patterns of new‐product concepts. The paper discusses the development of the model. It also discusses issues of measurement, estimation, testing, and implementation of the proposed approach based on actual empirical data.
INFLATION, MAINTENANCE OF CAPITAL, AND THE IRR MODEL: AN APPRAISAL AND ALTERNATIVE
Authors: Hartley Ronald V.
Published: June 2007

Capital budgeting under inflationary conditions presents some additional implementation problems when computing the internal rate of return. This paper reviews an earlier proposal made in this journal and concludes that it has some technical deficiencies. Further, it does not have the flexibility needed to be congruent with a wide variety of concepts of capital maintenance and asset evaluation. An algorithm is developed that will permit the user to make a variety of assumptions and then solve for the IRR that is consistent with those assumptions.
ORTHOGONAL INFORMATION STRUCTURES—A MODEL TO EVALUATE THE INFORMATION PROVIDED BY A SECOND OPINION
Authors: Ahituv Niv , Ronen Boaz
Published: June 2007

The paper discusses the value of information when a number of independent sources provide information related to a common set of states of nature. The starting point is the information economic model of information structures. The model is augmented to represent independence of informational sources by means of orthogonality of the information structures.

A new mathematical operator, orthogonal product, is defined and its properties are probed. It is shown that this operator maintains some mathematical properties such as closure, association, unity element, null element, and so forth. It is demonstrated how the orthogonal product represents the notion of multisource information.

The paper proves that an orthogonal product is generally more informative than its multipliers, namely, if cost is not considered a constraining factor, then there is a nonnegative value to obtaining a second opinion. An appendix to the paper expands this result to a case of partially dependent signals. The paper concludes with a numerical example and a discussion of the model's applicability for practical problems such as cost estimates.
REPETITIVE LOTS: FLOW‐TIME REDUCTIONS THROUGH SEQUENCING AND DYNAMIC BATCH SIZING
Authors: Jacobs F. Robert , Bragg Daniel J.
Published: June 2007

This paper presents a new integrative concept for job sequencing, dispatching, and lot sizing. The interrelation between these procedures and their impact on flow‐time performance is examined in a capacitated production environment. Generally, lot‐sizing decisions are made without regard to shop conditions and do not consider their impact on job sequencing procedures. The repetitive lots (RL) concept (developed and tested in this paper) attempts to integrate these decision processes.

RL uses a number of features which have not been considered jointly in either the lot‐sizing or job‐dispatching/sequencing literature. These include operation batch sizes which vary by operation, transfer of work within the shop in quantities less than operation batch size, and the use of overlapped operations. A simulation model is used to analyze flow‐time characteristics in a hypothetical production system. Traditional measures of flow‐time performance are compared to a set of nontraditional measures which capture the interaction between lot sizing and the sequencing procedure used.
FOUR APPROACHES TO THE CLASSIFICATION PROBLEM IN DISCRIMINANT ANALYSIS: AN EXPERIMENTAL STUDY*
Authors: Joachimsthaler Erich A. , Stam Antonie
Published: June 2007

Four discriminant models were compared in a simulation study: Fisher's linear discriminant function [14], Smith's quadratic discriminant function [34], the logistic discriminant model, and a model based on linear programming [17]. The study was conducted to estimate expected rates of misclassification for these four procedures when observations were sampled from a variety of normal and nonnormal distributions. In contrast to previous research, data were taken from four types of Kurtotic population distributions. The results indicate the four discriminant procedures are robust toward data from many types of distributions. The misclassification rates for both the logistic discriminant model and the formulation based on linear programming consistently decreased as the kurtosis in the data increased. The decreases, however, were of small magnitude. None of these procedures yielded statistically significant lower rates of misclassification under nonnormality. The quadratic discriminant function produced significantly lower error rates when the variances across groups were heterogeneous.
MATCHED PAIRS DISCRIMINATION: METHODOLOGY AND AN INVESTIGATION OF CORPORATE ACCOUNTING POLICIES
Authors: III Hunt Herbert G. , Ord J. Keith
Published: June 2007

The matched‐pairs methodology is becoming increasingly popular as a means of controlling extraneous factors in business research. This paper develops discriminant procedures for matched data and examines the properties of these methods. Data from a recent study by Hunt [14] on the determinants of inventory method choice are used to contrast the performance of the different methods. While all of the methods yield the same set of discriminating variables, those procedures that allow for the dependence among observations within a pair provide greater classificatory power than traditional multivariate techniques.
MAXIMIZING THE PROBABILITY OF ACHIEVING A TARGET PROFIT IN A TWO‐PRODUCT NEWSBOY PROBLEM*
Authors: Lau Amy Hing‐Ling , Lau Hon‐Shiang
Published: June 2007

This paper explores the two‐product newsboy problem. Solution procedures are developed to find the optimal production quantities of each product that will maximize the probability of achieving a profit target. The problem is shown to be surprisingly challenging, and numerical results obtained for only the more restrictive cases exhibit interesting behavior with important decision implications. For example, the results suggest that, if a firm has two single‐product divisions and each will receive a bonus for achieving a profit target, it is beneficial for the two divisions to cooperate if the targets are lax and the profit margins are high, but not if the targets are tight and the profit margins low. Also, between two products having different profit margins, one should produce more of the product with the lower profit margin if the target is sufficiently lax. This exploration motivates further efforts in solving the two‐product problem for the more general cases and also in extending the problem to three or more products.
JOINT PRODUCT COST ALLOCATION IN THE CONTEXT OF COST‐PLUS PRICING DETERMINATIONS WITH NON‐UNIFORM MARKUPS
Authors: Schneider Arnold , Jeroslow Robert G.
Published: June 2007

Companies that use cost‐based pricing sometimes manufacture products that involve joint cost allocation. A problem with this is that, while product prices are a function of the full cost, joint cost allocation methods using net realizable values depend on the product prices. This paper demonstrates that when all costs and production quantities are known or can be budgeted, it is possible to simultaneously determine unique product prices (having non‐uniform markup rates) and cost allocations using the net realizable value method.
A Multivariate Methodology for Simultaneously Capturing and Clustering Judgment Policies
Authors: Glorfeld Louis W. , Fowler George C.
Published: June 2007

This paper presents a new linear model methodology for clustering judges with homogeneous decision policies and differentiating dimensions which distinguish judgment policies. This linear policy capturing model based on canonical correlation analysis is compared to the standard model based on regression analysis and hierarchical agglomerative clustering. Potential advantages of the new methodology include simultaneous instead of sequential consideration of information in the dependent and independent variable sets, decreased interpretational difficulty in the presence of multicollinearity and/or suppressor/moderator variables, and a more clearly defined solution structure allowing assessment of a judge's relationship to all of the derived, ideal policy types. An application to capturing policies of information systems recruiters responsible for hiring entry‐level personnel is used to compare and contrast the two techniques.
The Effects of an Interactive Graphics‐Based DSS to Support Problem Structuring
Authors: Pracht William E. , Courtney James F.
Published: June 2007

Graphical, interactive, problem‐structuring tools were devised and incorporated into a DSS. These tools were based on concepts of structural modeling and motivated by propositions and findings in memory theory and imagery theory. A laboratory study was then conducted to investigate the relationship between decision‐maker characteristics and use of the problem‐structuring aid. The experiment was designed to determine whether use of the tool to assist in problem formulation led to a better understanding of problem structure.

A moderately complex management simulation and its companion DSS were used in the experiment. Eighty‐four subjects were divided into two groups: a control group that did not use the Graphical Interactive Structural Modeling Option (GISMO), and an experimental group that did. The results showed a statistically significant effect between cognitive ability and use of GISMO. Field independents (i.e., high cognitive ability) effectively combined GISMO use with image processing skills to understand the structure of the problem domain, but field dependents (i.e., low cognitive ability) were ineffective. There was very little difference in problem understanding in field dependents who used the tool and those who did not.
Analysis and Approximation of a JIT Production Line*
Authors: Jordan Scott
Published: June 2007

Production lines are often modeled as queueing networks with finite inventory between each stage. Little is known, however, about the average production rate and inventory levels when the service distribution at each stage is normal. This paper approximates the service distribution using iterative methods rather than simulation. The results show that iterative methods are useful when the problem is small and that approximation of the service distribution, by another distribution with the same mean and variance, is valid for steady‐state results such as average production rate or average inventory level.
Optimal Portfolio Selection and Cutoff Rates of Security Performance: A Multi‐Index Case*
Authors: Kwan Clarence C. Y.
Published: June 2007

The present study performs portfolio analysis using a multi‐index model in the diagonal form. In a mean‐variance framework, an alternative solution to a portfolio optimization problem is derived, providing analytical and computational improvements. This leads to a proof of a crucial functional property of cutoff rates of security performance in the solution, thus providing formal justification for a nonranking procedure of optimal portfolio selection. The robustness of the above functional property, and hence the nonranking procedure, is demonstrated numerically when the underlying normality assumption of security returns is replaced by a more general assumption of stable Paretian distributions.
Least Absolute Value Regression: Necessary Sample Sizes to Use Normal Theory Inference Procedures*
Authors: Dielman Terry , Pfaffenberger Roger
Published: June 2007

Recently developed large sample inference procedures for least absolute value (LAV) regression are examined via Monte Carlo simulation to determine when sample sizes are large enough for the procedures to work effectively. A variety of different experimental settings were created by varying the disturbance distribution, the number of explanatory variables and the way the explanatory variables were generated. Necessary sample sizes range from as small as 20 when disturbances are normal to as large as 200 in extreme outlier‐producing distributions.
Open Order Rescheduling in Job Shops with Demand Uncertainty: A Simulation Study
Authors: Christy David P. , Kanet John J.
Published: June 2007

This paper addresses the problem of open order rescheduling in a job shop. Results are reported of experiments conducted in a simulation model of an 8‐machine job shop. Four different order updating policies are examined. The due‐date process is modeled to include several realistic features about the pattern of due‐date variability. These features are parameterized and tested at several levels. Tardiness results indicate that open order rescheduling is beneficial only when allowances are loosely set. The results indicate that inventory performance is improved by order rescheduling, particularly in cases when due dates are revised to earlier times than originally forecast.
Transportation Approach to Locating Plants in Relation to Potential Markets and Raw Material Sources
Authors: Das Chandrasekhar , Heragu Sunderesh
Published: June 2007

Proximity to the market place has been considered the most important locational factor in the literature so far. However, the growing need for frequent deliveries of materials in smaller lot sizes for just‐in‐time (JIT) manufacturing prefers plants closer to the raw materials sources. Locating plants for JIT manufacturing is, therefore, a problem of finding the right balance between the requirements of procurement and distribution. A comprehensive model is proposed in this paper to solve this problem. The model is solved by using the transportation algorithm and produces simultaneous decisions on procurement, production, and distribution. The model does not require plant sizes to be known a priori, but it allows upper limits to be placed on the size of each plant and raw material source. As such, optimal plant capacities along with the corresponding procurement and distribution quantities are all determined by the model solution.
All‐Units Discounts for Standard Container Sizes
Authors: Knowles Thomas W. , Pantumsinchai Pricha
Published: June 2007

Some vendors offer their products to a purchaser in various container sizes. Normally, vendors will offer larger all‐units discounts on larger container sizes. Two algorithms have been developed in this paper to solve for the optimal number of each container size and the order quantity for the deterministic economic order quantity (EOQ) situation. The first algorithm, based in part on the dynamic programming solution to knapsack problems, solves the general case. The second algorithm, based in part on the dominance relations inherent in the pricing schedule, solves the more restricted case in which the purchaser is forced to accept the discount in the following manner. An order must be filled with containers of successively smaller sizes, beginning with the largest size. The purchaser is forced to accept the largest discount first, then the next largest, and so on.