bluuebunny/crossref_metadata_2025_split huggingface dataset:
AN EXPERIMENTAL COMPARISON OF STATISTICAL AND LINEAR PROGRAMMING APPROACHES TO THE DISCRIMINANT PROBLEM
Authors: Bajgier Steve M. , Hill Arthur V. 
Published: June 2007

ABSTRACTThis paper reports the results of an experimental comparison of three linear programming approaches and the Fisher procedure for the discriminant problem. The linear programming approaches include two formulations proposed by Freed and Glover and a newly proposed mixed‐integer, linear goal programming formulation.Ten test problems were generated for each of the 36 cells in the three‐factor, full‐factorial experimental design. Each test problem consisted of a 30‐case estimation sample and a 1,000‐case holdout sample. Experimental results indicate that each of the four approaches was statistically preferable in certain cells of the experimental design. Sample‐based rules are suggested for selecting an approach based on Hotelling's T2 and Box's M statistics.Subject Areas: Statistical Techniques, Linear Statistical Models, and Linear Programming.
MODELING LEARNING CURVE AND LEARNING COMPLEMENTARITY FOR RESOURCE ALLOCATION AND PRODUCTION SCHEDULING*
Authors: Chen Joyce T. 
Published: June 2007

ABSTRACTResearch on learning effects in mathematical programming models for optimum resource allocation has called attention to the difficulty in solving such models in their original nonlinear form. In this paper, systematically varying sizes of linear segments are designed to approximate productivity changes along the learning curve, and a single separable linear programming model is developed. With production complementarity and learning transmission between products, a more realistic resource allocation and production scheduling problem emerges. Two cases of learning transmissions are considered, and the model design process, which defines a decision problem that can be solved by a simplex algorithm, is demonstrated.
A MULTIATTRIBUTE DECISION‐MAKING APPROACH TO THE SELECTION OF AN AUXILIARY DEVICE FOR ICEBREAKERS*
Authors: Hannan Edward L. , Smith Joseph A. , Gilbert G. Ronald 
Published: June 2007

ABSTRACTThis paper describes the use of multiattribute decision making by the U.S. Coast Guard when choosing the most appropriate auxiliary device to use on an icebreaker. Five different missions of icebreakers are defined, and the objectives and attributes that describe the effectiveness of each auxiliary device in accomplishing these missions are established. For each geographical area of interest, the missions are weighted using the analytical hierarchy process. Also, group utilities are developed for attribute vectors in order to incorporate the judgments of different icebreaker operators.
TOWARD UNDERSTANDING THE CONTENTS OF THE “BLACK BOX” FOR PREDICTING COMPLEX DECISION‐MAKING OUTCOMES
Authors: Holt Robert N. , Scarpello Vida , Carroll Raymond J. 
Published: June 2007

ABSTRACTThe purpose of this research is to show the usefulness of three relatively simple nonlinear classification techniques for policy‐capturing research where linear models have typically been used. This study uses 480 cases to assess the decision‐making process used by 24 experienced national bank examiners in classifying commercial loans as acceptable or questionable. The results from multiple discriminant analysis (a linear technique) are compared to those of chi‐squared automatic interaction detector analysis (a search technique), log‐linear analysis, and logit analysis. Results show that while the four techniques are equally accurate in predicting loan classification, chi‐squared automatic interaction detector analysis (CHAID) and log‐linear analysis enable the researcher to analyze the decision‐making structure and examine the “human” variable within the decision‐making process. Consequently, if the sole purpose of research is to predict the decision maker's decisions, then any one of the four techniques turns out to be equally useful. If, however, the purpose is to analyze the decision‐making process as well as to predict decisions, then CHAID or log‐linear techniques are more useful than linear model techniques.
ECONOMIC ORDER QUANTITIES WITH QUANTITY DISCOUNTS: GRANDMA DOES IT BEST
Authors: Rubin Paul A. , Dilts David M. , Barron Beth A. 
Published: June 2007

ABSTRACTWe examine a new algorithm developed by Kuzdrall and Britney [5] for locating the optimal order quantity in the presence of quantity discounts. Their algorithm, based on a model for the supplier's formulation of the price schedule, involves a regression analysis to identify the supplier's variable cost per unit and the fixed cost that the supplier seeks to recover, followed by an iterative search for the optimum. The authors describe this method as a “convenient alternative to the aimless searching of traditional approaches” [5, p. 101]. We examine the allegation of superiority of their total setup lot‐sizing model over the classical method and dispute their claim of superiority.
SMALL PANELS OF EXPERTS IN DICHOTOMOUS CHOICE SITUATIONS*
Authors: Nitzan Shmuel , Paroush Jacob 
Published: June 2007

ABSTRACTThis paper analyzes an expert resolution problem under an uncertain dichotomous choice situation. The experts share a common system of norms and therefore they all prefer the alternative that best suits their purpose. The selection of such an alternative is referred to as a correct choice. Our analysis of optimal decision rules for panels of independent experts is pursued for n‐member decision‐making bodies, n≤ 5. The suggested optimality criterion is the maximization of the probability of the panel's making the correct choice. Within our framework, this criterion is equivalent to the more common criterion of expected‐utility maximization. For three‐member panels of experts, the expert resolution problem is solved and illustrated by means of a medical application. For four‐member panels, we list the three relevant decision rules, specify the conditions for all possible rankings of these rules, and, finally, present an extended consulting application. We conclude by listing seven relevant decision rules in the case of five‐member decision‐making bodies.
COMPLEX MULTIECHELON INVENTORY SYSTEM MANAGEMENT USING A DYNAMIC SIMULATION MODEL
Authors: Clark Thomas D. , Trempe Robert E. , Trichlin Herbert E. 
Published: June 2007

ABSTRACTA dynamic modeling approach to management of multiechelon, multi‐indenture inventory systems with repair is addressed. The structure of the model follows that of the U.S. Air Force Reparable Asset Management System. The model is used as a vehicle to discuss the structure of typical multiechelon systems and to illustrate the advantages of a dynamic modeling approach to such systems.
SIMULATION OF A CRISIS MANAGEMENT INFORMATION NETWORK: A SERENDIPITOUS EVALUATION
Authors: Belardo Salvatore , Pazer Harold L. , Wallace William A. , Danko William D. 
Published: June 2007

ABSTRACTAn experimental design responsive to a unique opportunity to evaluate the effectiveness of simulation as a training, research, and design environment for crisis management was developed when an actual crisis situation occurred less than a week after the authors had observed and evaluated a full‐scale training simulation. The crisis event at the Robert E. Ginna nuclear facility in upstate New York paralleled the simulation in location, content, and scope. The results reported in this paper are based upon a combination of personal interviews and the analysis of written communication logs. Hypotheses were tested concerning the predictive dimensions of the simulation with respect to individual descriptors related to stress and response capabilities, communication descriptors related to content and frequency, and network descriptors related to structure and utilization. The results are interpreted in the context of implications for training, research, and design.
SHAREHOLDER LIMITED LIABILITY AND MEAN‐VARIANCE MODELS OF CAPITAL STRUCTURE*
Authors: Rhee S. Ghon 
Published: June 2007

ABSTRACTThis paper demonstrates that shareholder limited liability imposes a restriction on corporate borrowing and that failure to incorporate this restriction into the analysis yields the “reductio ad absurdum” argument against mean‐variance models of optimal capital structure. With corporate income taxes and costless bankruptcy, the firm's value is a monotonically increasing function of debt as long as the amount of debt does not exceed the upper limit imposed by shareholder limited liability. As a result, the introduction of costly bankruptcy into the mean‐variance framework is justified.
COMPARATIVE EVALUATION OF INFORMATION UNDER TWO BUSINESS OBJECTIVES
Authors: Ahituv Niv , Wand Yair 
Published: June 2007

ABSTRACTInformation economics models evaluate the value of information under the assumption that decision makers wish to maximize their expected payoff. This assumption has been criticized for not being realistic enough since decision makers usually consider more than one business objective and might be satisficers rather than optimizers.This paper attempts to apply an information economics model to decision situations where two business performance criteria, expected payoff and risk, are considered. In order to overcome the difficulty of unknown trade‐off between the two criteria, one criterion is used as an objective to be optimized, while the other is set as a constraint. This may be interpreted as a combination of optimizing and satisficing approaches. It is shown how an information system can be evaluated in terms of both expected payoff and risk. The model suggests the trade‐off between the two criteria as an additional trait of an information system. In the last part of the paper, a numerical example illustrates how a comparative evaluation of information structures is performed when risk minimization and expected payoff maximization are concurrently used as business performance criteria.
THE RELEVANCE OF STATE‐UNIVERSITY RETIREMENT PLANS IN JOB SELECTION
Authors: Jacobs Fred A. , Watkins Frank E. 
Published: June 2007

ABSTRACTDocuments provided newly hired faculty members were requested from the major statesupported university in each of the fifty states. Those documents revealed two basic types of retirement plans: (1) state‐controlled, defined‐benefit plans in which retirement benefits are a function of a formula rather than the contributions by the employee and employer, if any; and (2) third‐party, defined‐contribution, input‐based plans in which the funds are controlled by a third party and the benefits depend upon the amount of contributions and the return earned by them. The analysis focused upon the defined‐benefit formula plans and a standard was developed to facilitate analysis. The simulations undertaken reveal significant, decision‐relevant biases—especially against faculty who elect to change employers as infrequently as once every ten years when different pension plans are involved! The risks attendant to each type of plan and possible career strategies are discussed.
ASSESSING ENVIRONMENTAL SCANNING AT THE SUBUNIT LEVEL: A MULTITRAIT‐MULTIMETHOD ANALYSIS*
Authors: Farh Jiing‐Lih , Hoffman Richard C. , Hegarty W. Harvey 
Published: June 2007

ABSTRACTEnvironmental scanning activities of over 400 top management subunits in 108 European manufacturing firms provided the data base for this research. Four traits (constructs) of scanning using three methods (interest, frequency, and time) were examined. A confirmatory factor analysis approach to multitrait‐multimethod (MTMM) data was employed. Verification of the reliability as well as convergent and discriminant validity of the scanning scales are reported and discussed. The viability of confirmatory factor analysis in providing a precise analysis of partitioning variance according to trait, method, and error is demonstrated.
A DECISION THEORY EXAMPLE IN FOOTBALL
Authors: Janssen C. T. L. , Daniel T. E. 
Published: June 2007

ABSTRACTIn the 1967 Harvard‐Cornell football game, Harvard was ahead 14–0 late in the game when Cornell scored two touchdowns. On both occasions, Cornell tried and failed on the two‐point conversion attempt and lost the game 14–12. Postgame arguments were divided on the merits of Cornell's strategy. For this frequently occurring scenario in college football, we derive a maximum expected utility decision rule for the decision of kicking versus running/passing based on the relative utility of a win, a tie, or a loss and the probabilities of success with a kick as opposed to a run/pass.
OPTIMAL DIMENSIONS OF VIRGIN STOCK IN CUTTING GLASS TO ORDER
Authors: Diegel Adolf , Bocker Hans J. 
Published: June 2007

ABSTRACTGlass cutting is a two‐dimensional version of the cutting‐stock problem. It involves two questions. One concerns the best way to cut a pane from a given plate. A less obvious question concerns selection of the plate from which the pane is cut. This leads to the question of what stock to order, before we even think of cutting it. We show that this latter question is more critical to economic cutting than the refinement of cutting procedures. We also present a method for selecting optimal stock sizes.
SOME COMMENTS ON “A SYSTEMS PERSPECTIVE ON MATERIALS REQUIREMENTS PLANNING”*
Authors: Heyl Jeff E. , Callarman Thomas E. 
Published: June 2007

ABSTRACTWe believe there are some serious deficiencies in the Morecroft article on MRP problems which appeared in a recent issue of this journal. The article, at the most, shows that MRP, inappropriately imposed on an existing production system, can result in undesirable system performance. This does not represent a new or startling conclusion. Four problem areas in the article are discussed, and suggested alternative approaches are offered.
CHOICE‐CONSTRAINED CONJOINT ANALYSIS
Authors: DeSarbo Wayne S. , Green Paul E. 
Published: June 2007

ABSTRACTChoice‐constrained conjoint analysis (CCCA) is a new method for metric conjoint analysis studies. It computes part‐worth utility functions that account for “revealed preference”—those products a respondent actually selects in an independent choice situation. CCCA uses an iterative penalty function estimation procedure that successively modifies initial regressionderived part worths so that respondent choices (either actual or intended) of real brands are predicted as accurately as possible.The paper first describes the motivation and rationale for CCCA and presents the mathematics of the algorithm. As an illustration, it applies the CCCA model and penalty function estimation procedure to a limited set of synthetic data. A second application of the technique is presented that uses data obtained by a major telecommunications firm that used conjoint analysis to examine the importance of several features of residential communication devices. The paper also discusses potential extensions of the CCCA model and the kinds of marketing applications for which it might be useful.
A MATHEMATICAL PROGRAMMING MODEL FOR FACULTY COURSE ASSIGNMENTS
Authors: McClure Richard H. , Wells Charles E. 
Published: June 2007

ABSTRACTThis 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

ABSTRACTCritics 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

ABSTRACTThe 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

ABSTRACTThis 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

ABSTRACTApplication 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

ABSTRACTA 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

ABSTRACTThe 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

ABSTRACTThis 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

ABSTRACTExperiments 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

ABSTRACTLivingston 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.