bluuebunny/crossref_metadata_2025 huggingface dataset:
AN ANALYSIS OF PERSONAL CHARACTERISTICS RELATED TO PROFESSIONAL STAFF TURNOVER IN PUBLIC ACCOUNTING FIRMS1
Authors: Rhode John Grant , Sorensen James E. , Lawler Edward E.
Published: June 2007

A sample of graduate and undergraduate degree holders in accounting are being studied during the first five years of their public accounting careers. Data on the biographical characteristics, vocational interests, and personality factors are analyzed in this study to discover if different profiles exist for those who remain with their firm of original employment in public accounting following graduation and those who find new positions. A number of significant differences were found. The findings should be of benefit to educators and representatives from the accounting profession because of their mutual concern with recruiting, staff development and retention, and academic preparation and career counseling.
CHOICE DILEMMA AS A PREDICTOR OF GROUP RISK BEHAVIOR1
Authors: Brown Stewart L. , McCollough W. Andrew
Published: June 2007

Interest in the Choice Dilemma Questionnaire (CDQ) has centered around the risk shift paradigm rather than around using the CDQ as a measure of an individual's risk preferences. Using 45 lower and middle management bankers as subjects in a computer‐based simulation game, the authors found a significant relationship (p < .05) between risk propensity of group members and an independent measure of group risk behavior. Thus, the CDQ may be a more general measure of risk preference than is commonly assumed.
ON THE DESIGN OF HIERARCHICAL PRODUCTION PLANNING SYSTEMS
Authors: Bitran Gabriel R. , Hax Arnold C.
Published: June 2007

To provide effective managerial support for decisions related to production planning and scheduling processes, it is useful to partition the set of decisions into a hierarchical framework. In the resulting system, higher level decisions impose constraints on lower level actions, and lower level decisions provide the necessary feed‐back to reevaluate higher level actions. The purpose of this paper is to suggest optimum procedures to deal with the resulting subproblems and to analyze the interaction mechanisms among the different hierarchical levels. Computational results are given.
A SIMULTANEOUS PLANNING MODEL FOR PRODUCTION AND WORKING CAPITAL*
Authors: Baker Kenneth R. , Damon William W.
Published: June 2007

A simultaneous model is proposed for the planning of production, inventory, workforce, and working capital levels over several periods. By exploiting the capabilities of linear programming, the model provides relevant information more efficiently than would be typical of the more traditional approach, in which planning is decomposed along functional lines. A detailed example is presented in order to illustrate the advantages of the simultaneous model.
HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS
Authors: Glover Fred
Published: June 2007

This paper proposes a class of surrogate constraint heuristics for obtaining approximate, near optimal solutions to integer programming problems. These heuristics are based on a simple framework that illuminates the character of several earlier heuristic proposals and provides a variety of new alternatives. The paper also proposes additional heuristics that can be used either to supplement the surrogate constraint procedures or to provide independent solution strategies. Preliminary computational results are reported for applying one of these alternatives to a class of nonlinear generalized set covering problems involving approximately 100 constraints and 300–500 integer variables. The solutions obtained by the tested procedure had objective function values twice as good as values obtained by standard approaches (e.g., reducing the best objective function values of other methods from 85 to 40 on the average. Total solution time for the tested procedure ranged from ten to twenty seconds on the CDC 6600.
SAMPLING AS A SOLUTION METHODOLOGY
Authors: Mabert Vincent A. , Whybark D. Clay
Published: June 2007

This paper examines the use of sampling procedures as a solution methodology for large combinatorial problems. Three sampling strategies are investigated: random sampling (each alternative is equally likely), biased sampling (alternatives' probabilities are biased by specified criteria), and improvement sampling (alternatives' probabilities are dynamically changed based upon new information). These three methodologies are illustrated and compared on the basis of solution quality and computer time requirements.
SOME IMPLICATIONS OF NIC BIDS ON SERIAL BOND ISSUES
Authors: Bierwag G. O.
Published: June 2007

Most state and local governments issue their debt in the form of serial bonds. These bonds are awarded on a competitive basis to the underwriter submitting the lowest “net interst cost”‐a specific measure of interest expense. This paper contains a description of a “pseudo‐dual” to the programming problem, used by underwriters, to prepare such bids. As such, the problem lends itself easily to a diagrammatic description. A further objective of this paper is to survey many constraints typically imposed on the NIC (net interest cost) problem by issuers. It is pointed out that these constraints usually increase the “net interest cost” so that the use of these constraints is an admission that “net interest cost” by itself is not regarded as the sole criterion of a good bid.
SIMULATION FOR FIRE DEPARTMENT DEPLOYMENT POLICY ANALYSIS
Authors: Monarchi David E. , Hendrick Thomas E. , Plane Donald R.
Published: June 2007

This paper discusses the use of simulation in the determination and analysis of alternative deployment strategies for urban fire supression systems. The simulation model utilizes the New York City‐Rand Institute simulator of fire department operations tailored for use with the Denver Fire department. A distinction is made between static deployment (where mathematical programming methods are used) and dynamic analysis (which employs the simulation model). The simulation model is described, as are its extensive data requirements.

The results discuss measures of validation of the simulation and outline the recommendations resulting from this research.
AN EMPIRICAL EVALUATION OF CONSTANT AND ADAPTIVE COMPUTER FORECASTING MODELS FOR INVENTORY CONTROL
Authors: Dancer Robert , Gray Clifford
Published: June 2007

This study compares the performance of one constant model with two adaptive models. MAD and bias were used as criteria for evaluating performance. The results of testing the adaptive models with the constant model were contrary to the expected better performance of the adaptive models; no significant differences were found between the models over known horizontal, trend, and seasonal demand patterns. However, some of the practical advantages of adaptive forecasting models in business suggest their continued use.
MATHEMATICAL PROGRAMMING FOR THE STATE EARMARKING PROCESS*
Authors: Simkin Mark G.
Published: June 2007

In state and local government, earmarking occurs when specific revenues from one or more tax imposts are set aside to fund specific expenditure programs. Problems arise in this dedication process when the theoretical link between the tax and expenditure program is doubtful or when tax receipts do not grow in proportion to desired expenditure patterns. This paper suggests that a long‐range mathematical programming model may be useful in ameliorating this latter “distortionary” aspect of the earmarking process. Extensions of the model, which permit exogenous financial assistance to the special fund, external lending and borrowing, intertemporal transfers of tax revenues or expenditure requirements, or constraints on tax increases or tax‐share burdens, are explored as ways to achieve an equitable as well as flexible tax policy.
A NOTE ON INTEGRATING INVENTORY AND PRODUCT SALES‐MIX MODELS
Authors: Reeves Gary R.
Published: June 2007

In a recent issue of Decision Sciences, Raiborn and Harris [2] discussed the integration of inventory and product sales‐mix models. While they formulated a model which reflected some of the interactions between product sales‐mix and inventory decisions, the purpose of this note is to point out deficiencies in their decision rule analysis for solving such integrated models.
ON THE SELECTION OF CRITICAL VALUES IN SEQUENTIAL DECISION PROBLEMS
Authors: Pappas James L. , Wichern Dean W.
Published: June 2007

This paper explores the effect which the choice of critical values in sequential decisions has on the overall distribution of payoffs. It demonstrates in the context of a simple two‐stage sequential decision model that the mean and variance of the overall distribution can be highly sensitive to the choice of critical values. Finally, it considers the problem of selecting optimal critical values when a standard meanvariance approach is used.
EMPIRICAL TESTS OF CONSTRAINED NONLINEAR OPTIMIZATION ALGORITHMS
Authors: Buffa Elwood S. , Ting Paul B.
Published: June 2007

A major difficulty in practicing constrained nonlinear optimization is that different optimization algorithms are effective for different classes of problems. The search algorithms tested were selected because they seemingly had the capability of solving ill‐defined problems. The emphasis of this research was on problems that are realistic and do not necessarily satisfy the classical assumptions of convexity, continuity, unimodality, etc. All algorithms were tested on a variety of problems. A problem was described by three types of attributes: the environmental attributes, the objective function attributes, and the constraint set attributes. The results of the study provide selective logic for choosing an effective search algorithm.
COMPARISON OF SEMI‐MARKOV AND MARKOV MODELS IN A PERSONNEL FORECASTING APPLICATION
Authors: Valliant Richard , Milkovich George
Published: June 2007

This paper reports an exploratory study of the development, application, and evaluation of a semi‐Markov model which forecasts personnel mobility rates within a major employer. The accuracy of the model is investigated by comparing the results generated by it to the results from a simple Markov model and to the observed behavior within the organization.
A DECISION MODEL FOR SELECTING ALTERNATIVE HYPOTHESES: AN EXTENSION*
Authors: Eckardt Walter L. , Aucamp Donald C.
Published: June 2007

A decision rule for selecting a one‐sided or two‐sided alternative for a standard hypothesis test is developed. Using a prior distribution of the parameter to be tested, the alternative is chosen which maximizes expected power. The test of a binomial parameter is presented to illustrate the method.
THE EFFECTS OF ENDORSEMENTS ON PRODUCT EVALUATION
Authors: Fireworker Robert B. , Friedman Hershey H.
Published: June 2007

This paper examines the effect of product endorsement claims on a consumer's decision making processes. A simulated endorsement claim was made for a product after which a consumer was presented with the product. Endorsements tested were the three most common types in use: celebrity, expert, and typical consumer, with two control groups for experimental design. Three scales of measurement were used to assess the effect of the endorsement: a consumer's intent to purchase, his overall attitude towards the product, and his expected price of the product. The results show the strength of celebrity and typical consumer endorsers. They also show that the endorser effect is dramatically weaker than hypothesized. The Lavidge‐Steiner hierarchy of advertising effects model is introduced in an attempt to explain this phenomenon. Guidelines for further research are provided.
SIMULATION AND SEWAGE
Authors: Mellichamp Joseph M. , Weaver Charles P.
Published: June 2007

Faced with increasing pressures on environmental issues, municipal and industrial planners must incorporate changing technology into planning processes. Conventional approaches to wastewater treatment plant design severely limit the ability of the designer to evaluate alternative design configurations. This paper suggests that computer simulation techniques can provide solutions to many of the problems which confront a designer. A simulation model of a hypothetical sewage treatment plant is described, and some of the design trade‐offs that can be evaluated with the model are presented.
A SPECTRAL MEASUREMENT OF THE CYCLICAL PATTERNS OF MULTIVARIATE TIME SERIES
Authors: Cho Dong W.
Published: June 2007

Although the diffusion and transmission of cyclical impulses are basic characteristics of economic and business activities, traditional studies of business cycles do not provide an effective measure of cyclical interaction. The purpose of this paper is to use spectral analysis to determine the cyclical patterns of multivariate economic and business time series. The proposed methodology was applied to the regional industrial diversification problem.
DYNAMIC COURSE SCHEDULING FOR COLLEGE FACULTY VIA ZERO‐ONE PROGRAMMING*
Authors: Shih Wei , Sullivan James A.
Published: June 2007

This paper formulates a multi‐period course scheduling problem as a zero‐one programming model. Under various constraints, and for a planning horizon of several terms, the model seeks to maximize: (1) the faculty course preferences in assigning faculty members to courses, and (2) the faculty time preferences in allocating courses to time blocks, via a two‐stage optimization procedure. The multi‐period structure of the model, strengthened by the explicit inclusion of a wide‐range of constraints designed to represent various special requirements has enabled the model to capture the many dynamic features of the course scheduling problem at the college level. As such, it can be used not only for long‐range or short‐range departmental planning, but also as a suitable framework toward the development of a larger, and all‐inclusive course scheduling decision system. The paper begins with a brief review of several related studies and then presents a multi‐period scheduling model and its extensions. Some numerical examples are used to test the model, and the authors' experience, resulting from such tests with several computer codes, is reported. The possible directions for future research are also suggested.
EDUCATION
Authors: Ahlund Mikael C. , Barksdale Hiram C. , Hilliard Jimmy E.
Published: June 2007

This paper illustrates how multivariate spectral analysis can be used to analyze complex, dynamic, business systems. Important temporal aspects of multiple time series are captured in the frequency domain by the coherence, phase, and gain statistics. A computer simulation of a time domain model produces sample results which demonstrate how the timing relations between two series can be reversed when the effects common to both series are partialled out. Finally, an empirical multivariate analysis of beef prices is used to determine the timing relations among prices at different levels of the production‐distribution system.
PERCEIVED ENVIRONMENTAL UNCERTAINTY AS A MEDIATOR OF EXPECTANCY THEORY PREDICTIONS: SOME PRELIMINARY FINDINGS
Authors: Ferris Kenneth R.
Published: June 2007

Expectancy theory has been tested in a variety of research settings with somewhat mixed results. One possible explanation for the sometimes low predictive ability of the model is the presence of environmental uncertainty. It was hypothesized that the greater the perceived environmental uncertainty, the greater the uncertainty regarding expectancy estimates. Hence, the predicted relationship between the level of motivation and job performance was expected to vary with the level of perceived uncertainty. Empirical results are presented supporting the hypothesis.
A SCREENING TEST FOR THE POISSON PROCESS
Authors: Hora Stephen C.
Published: June 2007

This paper presents a statistical test of the hypothesis that a time series has been generated by a Poisson process with a stable, but undetermined, intensity. The test has the virtues of easy application and economy with respect to data requirements.
THE DEMAND AND SUPPLY OF QUANTITATIVE METHODS DOCTORATES IN THE SOUTH
Authors: Render Barry , Wagoner William , Bobo James R. , Corliss Stephen
Published: June 2007

Of critical importance to educators, students, and their colleges and universities are the demand for and supply of new Ph.D.'s in the quantitative methods field. This study examines projected academic employment conditions, over the period 1977‐1981, for such doctorates in the southern region of the United States.
ON ESTIMATING PARAMETERS FOR BETA DISTRIBUTIONS
Authors: Kottas John F. , Lau Hon‐Shiang
Published: June 2007

The purpose of this paper is to comment on and give historical perspective to two methdologies for estimating parameters of beta distributions. Fielitz and Myers [3] [4] developed and advocated a methodology using the method of moments, while Romesburg [20] advocated a methodology usingthe method of maximum likelihood. However, what Fielitz and Myers presented as new research and suggested as an area needing further study is ground already trampled. The authors have prepared a graph to underline the superiority of the maximum likelihood method in fitting beta distributions.
A NOTE ON QUADRATIC PREFERENCES AND GOAL PROGRAMMING
Authors: Reeves Gary R.
Published: June 2007

In a recent article, Shim and Siegel discuss goal programming with quadratic preferences. In attempting to illustrate the solution of such decision problems, they obtain incorrect solutions to simple problems by complicated means. This paper points out the errors in the previously published manuscript.
HERESY IN DECISION ANALYSIS: MODELING SUBSEQUENT ACTS WITHOUT ROLLBACK *
Authors: Brown Rex V.
Published: June 2007

When making a current decision, like choosing an experiment, a subject will often take into account “subsequent acts” which he does not yet commit to. Common practice requires modeling through preposterior analysis, which treats one act as certain, conditional on the intervening information modeled. This is not logically necessary since the same expected utilities could be obtained by properly conditioning utility on any selection of events (including subsequent acts). The subject could assess utility marginal on subsequent acts or conditional on subsequent acts treated as uncertain events. The preposterior model is a special case of the latter where conditioning information is sufficiently modeled to imply subsequent act probabilities of zero or one. This paper argues that attempts at preposterior modeling are often unsuccessful and have critically flawed much current practice in decision analysis. Simpler approaches such as the “acts‐as‐events” model are intrinsically less dependent on restrictive assumptions and have been successfully applied to many real‐world decisions.
AUTOCORRELATED CASH FLOWS AND THE SELECTION OF A PORTFOLIO OF CAPITAL ASSETS *
Authors: Bey Roger P. , Singleton J. Clay
Published: June 2007

Capital budgeting models for analyzing real assets typically are based on a set of restrictive assumptions that influence financial managers' decisions and may prevent optimization of the firm's objectives. This research examines the common restrictive assumption that cash flows are intertemporally independent by first developing an economic state and simulation model based on a Markov process for including autocorrelated cash flows in the capital budgeting decision process and then demonstrating why managers should include autocorrelated cash flows in capital budgeting models by empirically testing the impact of assuming intertemporally independent cash flows on capital budgeting decisions. The results indicate that ignoring autocorrelated cash flows seriously limits the ability of capital budgeting models to provide optimal investment decisions. The model also is very attractive for practical application because it can be implemented with a minimum number of estimates and provides the set of input data required by a number of capital budgeting models. A discussion of the implementation of the model is included.
A COMPARATIVE ANALYSIS OF THE PREDICTIVE ABILITY OF ADAPTIVE FORECASTING, RE‐ESTIMATION, AND RE‐IDENTIFICATION USING BOX‐JENKINS TIME‐SERIES ANALYSIS ON QUARTERLY EARNINGS DATA
Authors: McKeown James C. , Lorek Kenneth S.
Published: June 2007

This paper assesses the predictive ability of the Box‐Jenkins methodology when utilized in an on‐going setting. Three procedures are utilized to update the original forecasts generated from the Box‐Jenkins models: adaptive forecasting, re‐estimation, and re‐identification. The results indicate that constant monitoring of the structure and parameters of the time‐series models are necessary through time. It appears that adaptive forecasting techniques are insufficient to update BJ time‐series models when used in conjunction with quarterly earnings data. Re‐estimation is recommended as each new observation becomes available. Re‐identification procedures are recommended on a less frequent basis.
DIFFERENCES IN ILL‐STRUCTURED PROBLEM SOLVING ALONG THE ORGANIZATIONAL HIERARCHY
Authors: Brightman Harvey J.
Published: June 2007

Problems are structured when they are repetitive, routine, and well‐defined. Standardized approaches including habit, tradition, standard operating procedures, and sophisticated analytical models are frequently used. Problems are ill‐structured when they are novel, one of a kind, unfocused, and complex. Depending on the level in the organization in which the ill‐structured problems occur, different problem‐solving processes may be utilized. The Dewey and Dewey‐Bentley models are proposed as general methodologies for solving operating problems at the lower levels of the organization. Simon's decision‐process trichotomy is proposed as a methodology for solving strategic problems at the upper levels of the organization. Allison's three conceptual models are suggested as descriptive frameworks for understanding Simon's decision process. Based upon Allison's work, a normative model of strategic problem solving is developed.
UNSUCCESSFUL IMPLEMENTATION THE CASE OF A COMPUTER‐BASED ORDER ENTRY SYSTEM
Authors: Lucas Henry C.
Published: June 2007

This paper discusses results of a longitudinal field experiment to evaluate the implementation of a computer‐based system. This new system includes the introduction of an optically scanned order input form and new computer programs. It is hypothesized that successful implementation would be affected by the quality of service and the personal costs and benefits to the users of the new system. The experimental results show a marked reduction in job satisfaction after implementation of the new system. The implications of the findings for the implementation of computer‐based systems in general are discussed.
OPTIMAL RENEGING DECISIONS IN A G/M/1 QUEUE
Authors: Parkan Celik , Warren E. H.
Published: June 2007

This paper is an analysis of the optimal reneging decision of a customer who joins a G/M/1 queue, having imperfect information about the queue. It is assumed that a customer receives a constant, known reward upon completion of service and incurs a cost proportional to the time spent in the queueing system. It is also assumed that a customer revises his estimated remaining waiting time in the system based on his initial estimate and observations of service time. Thus, a customer will renege when his estimated cost of remaining in the system exceeds his reward. The probability of a customer reneging during any given service is determined. Finally, it is shown how this probability varies with the parameters of the customer.
OPTIMAL INVENTORY STOCKING LEVELS WITH DEMAND TRANSFERENCE AMONG PRODUCTS
Authors: Matthews John P.
Published: June 2007

When a product is temporarily unavailable it is not uncommon to find consumers buying a related product rather than postponing the purchase until the former is back in stock. This phenomenon may be observed in the sale of cigarettes, candy bars, different‐sized packages of milk, lawn fertilizer, brands of wine and a host of other consumer items. This paper suggests a model for the vendor to employ when seeking to opti mize his stocking strategy for a periodic review/replenishment system.
THE EFFECTS OF GAME COMPLEXITY ON THE ACQUISITION OF BUSINESS POLICY KNOWLEDGE *
Authors: Wolfe Joseph
Published: June 2007

Certain cognitive and affective results obtained by three increasingly complex business games were examined. All simulations taught facts and concepts but the most complex simulation produced the greatest effect. More game complexity also brought about heightened challenge, lesser monotony, and greater decision‐making comprehensiveness. Motivational and learning levels, however, were not linearly positive with increasing complexity. The intermediate game was as motivating as the complex one although it was inferior to the simple game as a teaching device. The complex game also experienced higher student mortality.
A COMPUTER SIMULATION APPROACH TO THE TEACHING OF MAIL SURVEY STRATEGY ALTERNATIVES AND CHOICE
Authors: Burns Alvin C.
Published: June 2007

The author uses a computer simulation of mail questionnaire response rates to acquaint students with trade‐offs in terms of survey cost, accuracy, and time. In the absence of a theoretical base in the literature, the approach familiarizes students with current issues and problems, and helps to develop a decision‐making framework for this survey method. A step‐by‐step procedure emphasizing student involvement is described.
DESIGN OF AN M.B.A. SEMINAR ON THE IMPLEMENTATION OF OPERATIONS RESEARCH/MANAGEMENT SCIENCE *
Authors: Robey Daniel
Published: June 2007

This paper reports on an innovative seminar in which implementation of operations research and management science was the primary theme. Traditional educational strategies have sought to improve OR/MS acceptance by further exposing managers and management scientists to OR/MS techniques and management problems respectively. The present approach assumes that an understanding of the barriers to successful implementation and a knowledge of possible strategies for overcoming them are potentially more productive than the study of more OR/MS techniques. The seminar was designed to combine straightforward reading and discussion with empirical research on actual implementation situations. It is suggested that educators consider the value of this type of educational exercise in OR/MS curricula and M.B.A. programs.
COMMENTS ON GLOUDEMANS AND MILLER'S MULTIPLE REGRESSION ANALYSIS APPLIED TO RESIDENTIAL PROPERTIES
Authors: Brobst Robert , Gates Roger
Published: June 2007

Gloudemans and Miller [6] provide an interesting and useful application of regression analysis to the problem of residential property assessment. However, there are a number of problems with their model. These problems include: failure to consider the pitfalls of using stepwise regression in exploratory studies; failure to discuss levels of significance and appropriateness of signs of individual regression results; the use of ordinal data in the regression analysis; the use of an obscure and incorrect procedure for inflation adjustment; and, a general lack of a priori reasoning in the development and analysis of the article. These problems are discussed and possible remedies are considered.
MULTIPLE REGRESSION ANALYSIS APPLIED TO RESIDENTIAL PROPERTIES A REPLY
Authors: Gloudemans Robert J.
Published: June 2007

The reviewers' [1] comments generally relate to the design and development of multiple regression‐based appraisal models, a subject area of great promise and open to further research, although somewhat broader than the specific issues addressed in the authors' paper [5]. The purpose of this reply is to briefly restate the nature and conclusions of that paper and to offer comment upon the broader, more important, questions of model development raised by the reviewers.
TREATMENT PLANNING MODELS: AN APPLICATION *
Authors: Leonard Michael S. , Kilpatrick Kerry E.
Published: June 2007

This paper presents a systematic approach to treatment planning using an analytical model of the underlying decision‐making activity. Patient diagnostic classifications, augmented by a history of prior treatment applications, provide the state descriptions for a Markovian decision model of the treatment‐selection process. Patient records from four university dental clinics serve as the data base for model construction and validation.

This analytical model provides a means of duplicating the treatment plans of experts. Approximately 93% of the treatment planning model's treatment selections concurred with decisions made by two dental educators. Moreover, the models permit an examination of the critical considerations associated with therapy selection. This capability is discussed in terms of possible applications of the model in the practice of dentistry and in teaching.
A BEHAVIORAL STUDY OF NURSES, SUPERVISORS, AND DIAGNOSTICIANS IN A HOSPITAL SETTING
Authors: Lyon Herbert L. , Ivancevich John M.
Published: June 2007

A hospital is a highly complex organization that is based on the mutual cooperation of a large and heterogeneous mix of interdependent professionals, semiprofessionals, and nonprofessionals. The present study focuses upon role clarity, need for clarity, job satisfaction, and anxiety‐stress perceptions among administrators, nurses, and diagnosticians in a large and complex 450‐bed teaching‐referral hospital.
FORECAST MODIFICATION BASED UPON RESIDUAL ANALYSIS: A CASE STUDY OF CHECK VOLUME ESTIMATION
Authors: Mabert Vincent A.
Published: June 2007

The inability to identify all causal variables in a linear regression demand model may result in serial correlation which is generally considered undesirable; but it may be possible to take advantage of such an event. This case study, based upon Chemical Bank of New York, investigates the use of simple and exponential smoothing for modifying initial estimates from a regression model by using prior forecast error patterns to obtain better forecasts. The smoothing approaches are combined with a regression model to test for improved performance in predicting daily check volumes.
BARGAINING BEHAVIOR IN A BUSINESS SIMULATION GAME *
Authors: Slusher E. Allen , Sims Henry P. , Thiel John
Published: June 2007

Three studies of labor‐management negotiations were conducted within the context of a business simulation game. Face‐to‐face bargaining lasted approximately two hours and resulted in settlements that were incorporated into the simulation game parameters. A total of 56 simulated companies, each comprised of five MBA students, were studied. Results from the first study showed that extending low initial offers, extracting large first concessions, and making a high number of concessions were management bargaining tactics associated with obtaining a low wage rate. These findings were supported by study two. The third study found that an intrateam power mode of orientation was positively correlated with bargaining success and was negatively correlated with overall game success. The results support the use of a simulation game for teaching and research in bargaining.
OPTIMAL SELECTION OF MATCHED PAIRS FROM LARGE DATA BASES
Authors: Sibley A. M. , Burch E. Earl
Published: June 2007

This paper considers the problem of selecting matched pairs of observations for the reduction of bias in statistical hypothesis testing. A Euclidean distance function is suggested for measuring the similarity between paired observations. The matching process is then formulated initially as an assignment problem. Alternative formulations of the problem that would reduce computational difficulty are considered.
HEURISTIC LOT‐SIZING AND SEQUENCING RULES IN A MULTISTAGE PRODUCTION‐INVENTORY SYSTEM
Authors: Biggs Joseph R.
Published: June 2007

Material Requirements Planning (MRP) is currently being applied and used extensively in industry and is being proclaimed as the solution to many of the problems of traditional production‐inventory control problems. While the latter may be true, MRP is not without its own problems, two of which are the decisions concerning the appropriate lotsizing and sequencing rules to use in order to improve system performance. This paper describes a computer simulation study which was conducted to determine the effects of using various sequencing and lot‐sizing rules on various performance criteria in a multistage, multiproduct, production‐inventory system using MRP.

The results of the study indicate that the application of various rules causes changes in system performance and that an interaction effect exists between lot‐sizing and sequencing rules. What is more important is that a set of guidelines is developed to enable the practitioner to choose a lot‐sizing rule and a sequencing rule that will tend to improve the performance of his system for the various performance criteria.
EFFECTS OF LEARNING ON RESOURCE ALLOCATION DECISIONS
Authors: Liao Woody M.
Published: June 2007

Learning curves have important implications for managerial planning and control. This paper considers the effect of learning on managerial planning models for productmix problems that can be handled by a linear‐programming formulation. An approach to incorporate learning effects in the planning model is proposed in this paper. The feasibility and superiority of the proposed approach over the traditional approach are discussed through the use of a linear‐programming problem.
A STOCHASTIC DOMINANCE ORDERING OF SCHEDULING RULES
Authors: Weeks James K. , Wingler Tony R.
Published: June 2007

This paper applies stochastic dominance (SD) preference‐ordering criteria to job shop scheduling rules. A simulation model of a hypothetical dual‐constrained job shop is used to derive several measures of shop performance for a number of dispatching/due‐date scheduling policies. The results presented suggest that previous research conclusions concerning the relative performance of dispatching scheduling rules may need to be reconsidered if production schedulers are risk‐averse utility maximizers.
USE OF OPTIMIZATION AND SIMULATION MODELS TO ANALYZE OUTPATIENT HEALTH CARE SETTINGS*
Authors: Carlson Robert C. , Hershey John C. , Kropp Dean H.
Published: June 2007

An important problem facing the manager of an outpatient health care clinic involves determining the best combination of services, facilities, and personnel to maximize profits and simultaneously achieve acceptable measures of the clinic's daily performance. This problem is often attacked using either linear programming or computer simulation. This paper uses a recursive optimization‐simulation approach which takes advantage of the best features of both optimization and simulation while minimizing the disadvantages of each method used alone. Results from a hypothetical setting using data from several actual settings demonstrate the value of the recursive method.
MODEL FORMULATION FOR FLEET SIZE ANALYSIS OF A UNIVERSITY MOTOR POOL
Authors: Williams William W. , Fowler Oscar S.
Published: June 2007

A GPSS/360 model was developed to investigate the behavior of a university's motor pool dispatch fleet. Time‐series data were collected and frequency distributions were constructed for vehicle request patterns and trip‐duration times. Regression analysis was performed to formulate trip mileage generators as functions of service time. Appropriate statistical goodness‐of‐fit tests were conducted to ascertain the extent of congruence between actual system behavior and expectations based on a number of theoretical distributions. Analysis of simulated response variables indicates that the model's internal structure reproduces reality to a high degree. Fifteen years of simulated experience were generated for six alternative fleet size configurations; results suggest that reductions in existing fleet capacity could be realized without effecting undue impairment in service levels.
A NOTE ON RENEGING DECISIONS
Authors: Parkan Celik
Published: June 2007

This note is an extension of the approach to the problem of reneging introduced in Parkan and Warren [1]. It is assumed customers consider joining an M/M/1 queuing system with a prior gamma distribution over the values of the mean service time. Thus, each customer has an initial estimate of his total waiting time in the system. The customers associate the same sunk value with the waiting time and obtain the same reward at service completion. Having joined a system each customer may consider reneging in view of his revision of his initial service time estimate based on service observations. The bounds on the stationary state probabilities for such a system are obtained and examples are provided to compare the cases with and without reneging.
TWO‐PIECE VON NEUMANN‐MORGENSTERN UTILITY FUNCTIONS*
Authors: Fishburn Peter C. , Kochenberger Gary A.
Published: June 2007

Thirty empirically assessed utility functions on changes in wealth or return on investment were examined for general features and susceptability to fits by linear, power, and exponential functions. Separate fits were made to below‐target data and above‐target data. The usual “target” was the no‐change point.

The majority of below‐target functions were risk seeking; the majority of above‐target functions were risk averse; and the most common composite shape was convex‐concave, or risk seeking in losses and risk averse in gains. The least common composite was concave‐concave. Below‐target utility was generally steeper than above‐target utility with a median below‐to‐above slope ratio of about 4.8. The power and exponential fits were substantially better than the linear fits. Power functions gave the best fits in the majority of convex below‐target and concave above‐target cases, and exponential functions gave the best fits in the majority of concave below‐target and convex above‐target cases. Several implications of these results for decision making under risk are mentioned.
DECISION MAKING INVOLVING SEQUENTIAL EVENTS: SOME EFFECTS OF DISAGGREGATED DATA AND DISPOSITIONS TOWARD RISK*
Authors: Snowball Doug , Brown Clif
Published: June 2007

This paper concerns human processing of disaggregated data in a business decision setting involving sequential events. Subjects currently employed in trust banking institutions chose between two mutually exclusive alternatives in a series of decision trials. The outcome for each alternative was the result of a two‐stage process; an unsuccessful outcome resulted from failure at either the first or second stage. The probabilities of success at each stage and the overall (joint) probability of success were provided for each alternative. Participants showed strongest preferences for an optimal (expected‐value) strategy in processing the data; however, significant preferences for two suboptimal strategies also were observed. Preferences for suboptimal strategies were influenced by the magnitude of differences in the alternatives' joint probabilities of success, by the magnitude of differences in the alternatives' stage probabilities of success, and by subjects' dispositions toward risk.
CONFLICT RESOLUTION IN INVESTMENT DECISIONS: IMPLEMENTATION OF GOAL PROGRAMMING METHODOLOGY FOR DUAL‐PURPOSE FUNDS*
Authors: Kumar P. C. , Philippatos G. C.
Published: June 2007

Goal programming (GP) is designed to resolve allocation problems with conflicting goals. Both goals and constraints are incorporated in the allocational decision, and the objective function is stated in a way that, upon solution, yields a result “as close as possible” to the priority‐weighted goals. The present paper applies GP methodology to the investment decision of dual‐purpose funds (DPFs), that are required by law to pursue allocational decisions with potentially conflicting objectives. It provides an empirical demonstration that DPF managers could have improved their investment selection and subsequent performance by the use of GP methodology. Finally the paper stresses the importance of sensitivity analysis to improve both the goal‐ranking and target‐selection aspects of the methodology and provides a limited but illuminating empirical demonstration of post‐optimality analysis.
INTEGER GOAL PROGRAMMING IN ADVERTISING MEDIA SELECTION
Authors: Keown Arthur J. , Duncan Calvin P.
Published: June 2007

The media selection decision allocates advertising dollars among competing media so as to optimize promotional and corporate objectives. Linear programming attempts to model this process have been complicated by multiple and often conflicting management goals, the need for integer solutions, and nonlinearities. This study offers a technique that is sufficiently robust to simultaneously handle these problems. An alternative media selection framework is presented and the results of an illustrative application of integer goal programming are discussed. The proposed model improves on linear programming by success fully providing for optimal, integer solutions in settings that more realistically reflect the complexity of the media decision environment.
A GOAL PROGRAMMING MODEL FOR OUTPUT PLANNING
Authors: Fisk John C.
Published: June 2007

This paper describes a goal programming procedure for determining satisfactory output plans for a work center. The situation being modeled is one in which work center inputs are known but vary significantly across time periods. Input levels are fixed relative to a given master production schedule, and output levels can be varied only within certain prescribed limits, at least in the short term. The similarity of the output planning problem to the more familiar aggregate planning problem is noted and discussed.
BUSINESS COMBINATION DECISIONS: A U.S./CANADA STUDY*
Authors: Falk Haim , Gordon Lawrence A.
Published: June 2007

The purpose of this paper is to clarify the motives behind business combination decisions. Twenty‐one favorable characteristics associated with the motivations for business combinations were selected to serve as the basis for an empirical survey. Our analysis revealed that there are seven motivational variables of varying import and that the motivations underlying business combination decisions are similar for U.S. and Canadian executives.
A FUZZY SUBSET CHARACTERIZATION OF A SITE‐SELECTION PROBLEM
Authors: Narasimhan Ram
Published: June 2007

This paper presents an application of fuzzy subsets to the problem of selecting sites for locating gas stations. Cost minimization and profit maximization models represent typical approaches to location decisions. These approaches are not well‐suited to problems like site selection for gas stations because of the difficulty in identifying precise relationships, the uncertainties involved, and the qualitative and imprecise nature of much of the information used for decision making. This paper proposes the use of a model based on linguistic variables and a direct evaluation of the available alternatives via the use of fuzzy variables. Conclusions regarding the practical advantages and limitations of the approach are drawn based on the reported application.
ADAPTIVE CONTROL THEORY: SURVEY AND POTENTIAL APPLICATIONS TO DECISION PROCESSES*
Authors: Aoki Masanao
Published: June 2007

An important and distinct feature of a class of decision processes discussed in this paper is the possibility of gathering additional information between decisions and using it to improve future decisions. The analysis of these so‐called sequential decision processes is both complicated and far‐reaching in its implications. The purpose of this paper is to describe this class of decision processes to make its potential both more readily understood and better appreciated.
IMPLICATIONS OF THE BAKKE DECISION IN IMPLEMENTING AFFIRMATIVE ACTION PROGRAMS: A DECISION MODEL*
Authors: Solomon Robert J. , Messmer Donald J.
Published: June 2007

The U. S. Supreme Court decision in Regents of the University of California v. Allan Bakke (98. Su. Ct. 2733, 1978) provides guidelines to educational administrators regarding the implementation of affirmative action in student admissions. This paper presents a selection model which is consistent with the Supreme Court's decision in the Bakke case. This Diversity Model integrates traditional “ability” predictors with the illustrative diversity variables of sex and work history. The effect of the Diversity Model in terms of affirmative action impact and predicted grade point average when compared to a pure Performance Model and a Quota Model was evaluated on a sample of 199 MBA students. The Diversity Model did achieve an affirmative action effect with little or no sacrifice in student quality.
EMPIRICAL VALIDATION OF ELICITED UTILITIES FOR PREDICTION AND DECISION MAKING*
Authors: Barron F. Hutton
Published: June 2007

The HOPE (Holistic Orthogonal Parameter Estimation) elicitation procedure assesses multiattribute utility functions via sample holistic judgments. Analyses of actual judgmental data are presented that support two simple assertions: (1) HOPE‐derived utilities are valid and (2) the resulting utility functions are useful for decision making.
DATA ANALYSIS FOR SIMULATION EXPERIMENTS: APPLICATION OF A DISTRIBUTION‐FREE MULTIPLE COMPARISONS PROCEDURE
Authors: Cooley Belva J. , Cooley John W.
Published: June 2007

The analysis of simulation data in the evaluation of competing alternatives presents a problem for the analyst using conventional statistical techniques. The assumptions of normality and common variances generally cause difficulties since many classes of simulation experiments typically violate both of these assumptions. In addition, the analyst is usually interested in comparing competing alternatives using environments that are as close to identical as possible. In these situations, blocking is desirable and can usually be accomplished by using common random number streams. This paper discusses a distribution‐free method based on Friedman's rank sums test that can be used to analyze simulation results exhibiting the above characteristics. The procedure requires only independence within treatments.
ASYMMETRIC LOSS FUNCTION AND OPTIMAL POLICY UNDER UNCERTAINTY: A SIMPLE PROOF
Authors: Hosomatsu Yasu
Published: June 2007

Given an asymmetric quasi‐convex loss function and a symmetric quasi‐concave probability density function, both continuous, an extremely simple proof is suggested that shows that a policy maker will minimize expected loss by choosing a policy value on the less‐damaging side of the loss function. This proof, which is compatible with a wide variety of loss functions and probability density functions, is extended to include cases where a symmetric loss function is matched against an asymmetric probability density function and where an asymmetric loss is matched with an asymmetric probability density function.
A NOTE ON PROCEDURES FOR TESTING THE QUALITY OF A CLUSTERING OF A SET OF OBJECTS
Authors: Milligan Glenn W. , Mahajan Vijay
Published: June 2007

Despite the increased application of cluster analysis in decision sciences, few attempts have been made to derive hypothesis‐testing procedures for the evaluation of clustering solutions. In fact, the present paper shows that at least one such attempt failed to specify a meaningful sampling distribution for the test procedure. An alternative index based on the concept of point‐biserial correlation is proposed as a possible recovery measure. The index is subsequently used to form the basis of a valid statistical test for the existence of cluster structure.
SPECIFICATION AND ESTIMATION OF LOGICALLY CONSISTENT LINEAR MODELS
Authors: Koehler Gary J. , Wildt Albert R.
Published: June 2007

The implications of constrained dependent and independent variables for model parameters are examined. In the context of linear model systems, it is shown that polyhedral constraints on the dependent variables will hold over the domain of the independent variables when a set of polyhedral constraints is satisfied by the model parameters. This result may be used in parameter estimation, in which case all predicted values of the dependent variables are consistent with constraints on the actual values. Also, the implicit constraints that define the set of parameters for many commonly used linear stochastic models with an error term yield values of the dependent variables consistent with the explicit constraints. Models possessing these properties are termed “logically consistent”.