bluuebunny/crossref_metadata_2025_split huggingface dataset:
NATURE OF PROBLEM ILL‐STRUCTUREDNESS: IMPLICATIONS FOR PROBLEM FORMULATION AND SOLUTION
Authors: Taylor Ronald N. 
Published: June 2007

ABSTRACTThe distinction between ill‐structured and well‐structured decision problems is extended in this paper to include the degree of familiarity that a decision maker has with the initial state of the problem, its desired state, and appropriate transformations for resolving the problem. It is shown that problem ill‐structuredness may result from inadequate information regarding any of these components and that the nature of problem ill‐structuredness has important implications for problem formulation and solution. A decision tree is presented which represents strategies for either reformulating primary problems of each class of ill‐structuredness to a more readily solved form, or solving the problem as initially formulated.
SESAME STREET FOR DECISION SCIENCES
Authors: Hesse Rick 
Published: June 2007

ABSTRACTIn Part I, several problems confronting learning and teaching in Decision Sciences are examined and possible solutions presented. Students dislike and fear mathematics, treat it as a foreign language (a dead one at that), and are subjected to archaic teaching methods. Teachers suffer from poor training, incongruent goals, and inadequate models. As the popularity of the Decision Sciences dwindles, teaching becomes even more critical in our profession.In Part II, three designs for teaching operations research or statistics with organizational behavior are presented. These have all been implemented during the last three years. These designs attempt to take advantage of principles learned in organizational behavior to enhance the learning situation in the quantitative courses in decision sciences.
CONCEPTS, THEORY, AND TECHNIQUES
Authors: Fielitz Bruce D. , Myers Buddy L. 
Published: June 2007

The beta distribution is becoming more widely used in business applications and in economic model‐building. A simple way to estimate the parameters of the univariate distribution and the general multivariate distribution would be useful but there appears to be no simple way of accomplishing this task. For example, the method of maximum likelihood does not yield tractable results.The method of moments presented in this paper is a practical way to obtain parameter estimates for the beta distribution. Explicit estimators are derived for the univariate and bivariate case and estimators are then inferred for the n‐variate case. Empirical tests suggest that the method of moments may be used to establish useful estimates for these parameters. Also, estimates obtained by the method of moments may be used to develop bounds on the parameters so that computational techniques can be utilized with other estimation methods possessing more desirable properties.
SIMPLE MODELS FOR MONITORING NEW PRODUCT PERFORMANCE
Authors: Ayal Igal 
Published: June 2007

Several studies have shown that consumers trying a new brand of frequently purchased consumer goods behave differently from repeat buyers. The “customer mix” for a new brand changes over time. Early in a new brand's life, most of the buyers are triers, while later in its life, a significant portion of the buyers are repeaters. The study presented here tests the hypothesis that an aggregate sales forecast, “averaging” the behaviors of triers and repeaters, would be outperformed by a model that treats them separately.A new product model, giving separate consideration to triers and repeaters, is developed. This model is tested on predictive ability against a widely used single‐equation aggregate model. Consumer panel purchase diaries and data on advertising in measured media, covering a period of 42 months following introduction of a major brand of cold tablets, serve as the proving grounds. Data for the early part of this period serve as the data base for both models, while data for the rest of the period serve to test the predictive ability of both models. The disaggregate model is shown to perform significantly better than the aggregate model in terms of predictive accuracy. It also offers several other advantages in use as a decision aid, both for GO‐NO decisions and for marketing mix decisions.Finally, several problems in the implementation of the proposed model and implications for research strategy are discussed.
MOTIVATION AND MANAGEMENT CONTROL SYSTEMS
Authors: Livingstone J. Leslie , Ronen Joshua 
Published: June 2007

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.
INVENTORY MANAGEMENT AND CAPITAL BUDGETING: A PEDAGOGICAL NOTE
Authors: Thompson Howard E. 
Published: June 2007

This paper shows, through an alternative development of the lot size model, how the methods of capital budgeting can be logically applied to the determination of optimal inventory levels. There is no reason why inventory management needs be treated any differently than the management of fixed assets. The rule that the stock of fixed assets should be expanded until the marginal rate of return equals the marginal cost of capital results from maximizing the present value of profits as a function of the investment level. In a like manner, the “square root” formula from inventory theory results from maximizing the present value of profits as a function of the investment in inventory.In addition, formulating the inventory problem as a capital budgeting problem has advantages for incorporating deterioration, obsolescence, and other costs into the model in a more logical and less intuitive way.
LINEAR VS. NON–LINEAR MODELS OF THE FORMATION OF AFFECTIVE REACTIONS: THE CASE OF JOB ENLARGEMENT
Authors: Brief Arthur P. , Wallace Marc J. , Aldag Ramon J. 
Published: June 2007

ABSTRACTNumerous researchers have now considered the impact of task characteristics on employee responses. However, relatively little is known about how information regarding individual task dimensions is processed to arrive at an overall judgment. Most studies simply consider the role of individual job characteristics or arbitarily apply a particular combinatory model. In the rare instances where alternative models have been simultaneously considered, there has been some apparent confusion regarding the meaning of models and/or interpretation of findings.The current study explored alternative combinatory models of human evaluative judgments. Data on task dimensions and employee affective responses were collected from subjects in two samples, one in a manufacturing firm and one in a Division of Corrections. Task dimension scores were combined by use of compensatory, conjunctive, and disjunctive models. Multiple regression was used to examine relationships between resultant scores and various affective response indices.All three models exhibited generally significant predictive ability. The linear compensatory model was found to be as powerful a predictor of evaluative judgments as were non‐linear alternatives. Implications of findings are presented.
IMPROVING THE MEAN‐VARIANCE CRITERION USING STOCHASTIC DOMINANCE
Authors: LaCava Gerald J. 
Published: June 2007

ABSTRACTThe increased importance of the nonnormal stable Paretian distributions necessitates the development of an investment criterion which does not depend upon the mean and variance. This paper develops a criterion based upon the location and scale parameters of a probability distribution. The rationale of the criterion is established using stochastic dominance orderings of probability distributions. The paper also presents estimators for the location and scale parameters.
REGRESSION METHODOLOGY WITH GROSS OBSERVATION ERRORS IN THE EXPLANATORY VARIABLES***
Authors: Brecht H. David 
Published: June 2007

ABSTRACTThe robustness of linear programming regression estimators is examined where the disturbance terms are normally distributed and there are observation errors in the explanatory variables. These errors are occasional gross biases between one set of observations and another. The simulation of short series data offers preliminary evidence that when these biases have a non‐zero mean, MSAE estimation is more robust than least squares.
USING DUMMY VARIABLES TO CHECK FOR ROUNDING ERROR IN COMPUTERIZED REGRESSION PROGRAMS*
Authors: Mullet Gary M. , Morgan David L. 
Published: June 2007

ABSTRACTAfter a brief review of the role of dummy variables in regression analysis and the current state‐of‐the art in rounding/truncation error detection in computerized least squares programs, this paper presents a theorem that can be used to detect this type of error whenever an analyst is running a regression program that has one (or more) dummy variables as independent variables.
THE IMPACT OF ALTERNATE DECISION TECHNIQUES ON USER BEHAVIOR
Authors: Robey Daniel 
Published: June 2007

ABSTRACTThe quantitative disciplines have focused their efforts primarily upon more complete and efficient methods for analyzing decision problems. Almost totally neglected in these efforts is the interplay between a decision technique and its ultimate user. This interface is of crucial importance to the continued success of the decision sciences in organizations. Data are presented to support the contention that decision techniques and their resultant impact on job content interact with psychological variables to cause variation in user satisfaction and performance. These results are similar to the effects hypothesized to occur at blue collar levels in organizations.
ON FINDING AN INITIAL SOLUTION FOR THE DUAL SIMPLEX ALGORITHM
Authors: Steinberg David I. 
Published: June 2007

ABSTRACTTorrance [4] has proposed a “new” approach to finding an initial solution of a linear programming problem for use in conjunction with the dual simplex algorithm. The purpose of this note is to comment on two aspects of that paper. Firstly, Torrance's method is not new at all, but was proposed in 1958 by Wagner. Secondly, the method can be implemented much more efficiently than Torrance suggests.
THE APPLICABILITY OF THE MAXI–MIN PRINCIPLE TO PORTFOLIO SELECTION IN TERMS OF MEANS AND VARIANCES OF UNKNOWN DISTRIBUTIONS
Authors: Mantell E. H. 
Published: June 2007

ABSTRACTThis paper establishes two propositions which allow a risk‐a verse decision maker to apply a maxi‐min strategy in his portfolio selection. The strategy consists of selecting a portfolio in which the lower bound of the expected utility is maximized. The propositions have their greatest applicability in situations in which the investor knows the means and variances of the portfolio returns, but has no other knowledge relating to the probability distributions governing the rates of return.
SIMULATION OF INFORMATION CHOICE
Authors: Fellingham John C. , Mock Theodore J. , Vasarhelyi Miklos A. 
Published: June 2007

ABSTRACTBeginning with the information economics framework and a multi‐period decision model [15], this paper considers the use of computer simulation methods within an information system choice environment. Actual decision behavior is replaced by optimal decision rules, and simulation is used to evaluate the effects of parameter changes in the environmental model. Simulation is shown to be functional (1) in estimating the value of alternative information structures within a fifteen period decision model and (2) in providing sensitivity and statistical data which would be useful both for different decision maker utility functions and for a variety of information system design questions.
AGGREGATING EXPERT OPINION IN DECISION‐MAKING
Authors: Willis Raymond E. 
Published: June 2007

ABSTRACTIn using nominal groups for decision making, it is necessary to use some mechanical procedure for combining the evaluations. A simulation model is used to compare procedures for the case where a nominal group of m evaluators must select the best of n alternatives and where the evaluations are subject to random errors. Criteria are the probability of making a correct selection and the relative quality of the choice.
MULTIPLE REGRESSION ANALYSIS APPLIED TO RESIDENTIAL PROPERTIES
Authors: Gloudemans Robert J. , Miller Dennis W. 
Published: June 2007

ABSTRACTAn interesting and promising innovation in the assessment of property for tax purposes is the application of multiple regression analysis. Sales prices are regressed on various housing characteristics, and models developed from sold properties are used to generate value estimates for unsold properties. Two important issues relating to the development of such models are (1) the extent to which real estate markets are stable in terms of structural relationships over time, and (2) the extent to which sales prices reflect actual market values. The first issue is important because it affects how current sales must be before they can be used in model development, as well as the amount of information the assessor must collect and maintain on properties. The second issue is important because it concerns the amount of measurement error in the models and the extent to which the assessor/analyst can unambiguously interpret residual variance. These issues are investigated by comparing regression models developed from a sample of properties in Eugene, Oregon, which sold in each of two well separated time periods.
A STOCHASTIC MODEL FOR ANALYSIS OF VARIATIONS IN AIR POLLUTION LEVELS
Authors: Anthony Ted F. , Taylor Bernard W. 
Published: June 2007

ABSTRACTExamination of environmental data seems to suggest that variations in air pollution levels from one point in time to another tend to follow some form of observable pattern. In this article, the authors explore an approach to observing, describing and analyzing these variations. They develop a model which is essentially a Markov framework and use it to suggest a number of interesting questions and to facilitate their solution. In this demonstration, the focus is on a single component of air pollution, suspended particulate matter. For implementation, a model would need to incorporate other elements of the pollution mix. As the composition of air pollution differs from one air shed to another, so will the parameters of the model.
THE DOLLARS AND SENSE OF SIMULATION
Authors: Godin Victor B. 
Published: June 2007

ABSTRACTThis paper deals with the economics of computer simulation applied to problems in the operations management/industrial engineering area. First, the material in the literature dealing with the economics of simulation is summarized. However, the amount of information available on the economics of simulation is very small. A number of hypotheses are presented for this paucity of material. Since many managers operate in an environment in which costs and benefits are relevant to their decision‐making process, the lack of data on the economics of simulation may be a barrier to the utilization of the technique. In an attempt to improve this situation, a framework for the collection and specification of the economics of simulation modeling projects is proposed as a method of urging management scientists to begin to collect and publish data on the economics of simulation projects.
UNCERTAINTY RESOLUTION AND MULTI‐PERIOD INVESTMENT DECISIONS
Authors: Percival John , Westerfield Randolph 
Published: June 2007

ABSTRACTIt is demonstrated in this paper that early uncertainty resolution is preferred to delayed uncertainty resolution when comparing sets of uncertain cash flow sequences in an N‐period setting. The implicit and often unwarranted assumptions regarding uncertainty resolution which are made in the three widely used methods in capital budgeting problems are demonstrated. Finally, it is demonstrated that the generally accepted procedure for measuring uncertainty resolution is restrictive in its underlying assumptions.
CREDIT‐SCORING MODELS AND THE CUT‐OFF POINT—A SIMPLIFICATION
Authors: Beranek William , Taylor Walton 
Published: June 2007

ABSTRACTThe article presents a simple method for establishing the optimal cut‐off point on a credit‐scoring index under a variety of conditions. A procedure for choosing an index from several candidates is also proposed, and the use of credit information in such an index is discussed.
CORRECTING FOR THE INHERENT BIAS IN THE AVERAGE BIDDER APPROACH TO COMPETITIVE BID DEVELOPMENT
Authors: Kottas John F. 
Published: June 2007

ABSTRACTA key step in contract bid development is estimating the probabilities of winning with bids of various profit potentials. One of the most common approaches to estimating these probabilities, the average bidder approach, has an inherent bias which causes it to almost always over‐estimate the actual chances of winning. This note explores the nature of this error and suggests a method to compensate for it.
SENSITIVITY ANALYSIS WITH INTERACTION EFFECTS
Authors: Bentz William F. , Sherr Lawrence A. , Miller Robert E. 
Published: June 2007

ABSTRACTThe purpose of this paper is to extend the sensitivity analysis methodology as it applies to linear programming. The methodology developed herein is concerned with those changes in a technological coefficient that cause simultaneous changes in the relevant cost coefficients of the objective function. By proceeding from the definitions of feasibility and optimality, the authors develop formulas for determining bounds on the extent to which a technological coefficient, which has a predetermined effect on the corresponding cost coefficient, can vary without changing the optimal set of activities. After the formulas are developed, their use is demonstrated on a product‐mix problem. This technique is of interest because changes in the rate at which an input is utilized can be expected to change the cost per unit of a resulting product. This interdependence should be recognized whenever a sensitivity analysis is performed on a technological coefficient of either a cost minimization or a contribution margin maximization problem.
ADVERTISING EXPENDITURE TRAJECTORIES: AN EMPIRICAL STUDY FOR FILTER CIGARETTES 1953–1965
Authors: Turner Ronald E. , Wiginton John C. 
Published: June 2007

ABSTRACTIn an advertising strategy, it is preferable to optimize a sequence of periodic decisions, rather than optimizing each period's decision separately. Thus, a dynamic technique such as optimal control, which is used in this study, should be employed. Necessary conditions, as inferred from a parsimonious advertising model, are tested using data from the tobacco industry. Parameter estimation involves the use of non‐linear regression. The estimates permit trajectories of optimal advertising expenditures and optimal market shares to be constructed for filter cigarettes. When compared with the actual trajectories, the optimizing trajectories exhibit a striking correspondence to reality. Therefore, interesting results can be obtained using a simple model, provided the optimizing method takes into account the dynamic nature of managerial decision‐making and provided powerful methods for estimating model parameters are used.
A DECISION ANALYSIS APPROACH TO BUSINESS STATISTICS
Authors: Brabb George J. , Livingston E. Jeffery 
Published: June 2007

ABSTRACTThe general area of business statistics includes the coverage of three distinct subject areas: descriptive statistics, classical inference, and the more recently developed Bayesian decision procedures. Attempts at teaching these subjects has often produced confusion and a lack of confidence in statistical tools for many students. This article describes a unique way of teaching and presenting these three areas so that a student is given a framework for organizing and applying the different subject areas. The vehicle used to gain this framework is a simple decision model in which the various stages of the model provide excellent vantage points for introducing statistical tools. The key to the approach is to keep a student in a decision‐making environment. The tools and methods of the three areas are only introduced as they aid the analysis of the decision. This immediate application in a decision context motivates a student to learn the tool and visualize its use.
PROPOSALS FOR A PROGRAM OF EMPIRICAL RESEARCH INTO THE PROPERTIES OF TRIANGLES*
Authors: Christenson Charles 
Published: June 2007

ABSTRACTPhysical geometry is viewed in this essay as the prototype of a successful generalizing empirical science. Suppose that physical geometry had been studied in ancient Egypt by empirical methods similar to those commonly used today by many researchers seeking general propositions useful in explaining, predicting, or controlling phenomena of interest to practicing managers. Would these methods have produced valid and useful geometric generalizations? This intriguing question is explored in Part I by means of a parable which suggests a negative answer to the question. The reasons for this negative conclusion are developed in Part II. In the successful generalizing sciences, general propositions (or theory) have not been the result of an a posteriori“induction” from observational data, but rather the result of an a priori“construction” of a framework for the coordination of measurement operations. Such a framework, whether explicitly articulated or not, is a necessary condition for the collection of coherent and reproducible observational data and, therefore, for explanation, prediction, and control of phenomena. Yet, despite its a priori character, an acceptable framework or theory must be “empirical” in Popper's sense of being subject to refutation by observation. If the framework is logically prior to data, however, what is its source? In the successful generalizing sciences, it is argued in Part III, theories have been generalized not from data but from the skills—the coordination of operations—of practitioners. This genesis “explains” the success of the sciences, because an effective skill includes within itself tests of its range of applicability and adapts itself to changing conditions. A discussion of the implications of this argument for making management “scientific” concludes the essay.
ADDRESSING THE IMPLEMENTATION PROBLEM: A GAMING APPROACH
Authors: Davis K. Roscoe , Taylor Bernard W. 
Published: June 2007

ABSTRACTTraditionally decision sciences has been plagued with the problem of implementation, i.e., transforming a sound theoretical technique into an operational system. Most researchers who study the problem concentrate on identifying factors which relate to implementation or on identifying the change process required to achieve implementation. In a recent study, Sorensen and Zand [24] demonstrate that the Lewin‐Schein change theory explains the process necessary for achieving implementation.While the Lewin‐Schein theory explains the required change process, the theory does not address the question of how one brings about change. The purpose of this article is to describe a “gaming” approach for accomplishing change. A case example is given to demonstrate the proposed implementation methodology.
AN EFFICIENT METHOD FOR DETERMINING THE WAITING TIME DISTRIBUTION OF QUEUES
Authors: Lau Hon‐Shiang 
Published: June 2007

ABSTRACTThis paper presents a practical method for determining the waiting time distribution of a single‐stage queueing system for general distribution of inter‐arrival/service times. The method requires the matrix solution of Lindley's equation for waiting time distribution by treating time in discrete units. Some important characteristics of the method are: a) it is easily programmable; b) it has high accuracy; c) it has modest CPU time and storage requirements; and, d) it requires no mathematical functional form for inter‐arrival/service time distributions.