摘要:

ABSTRACTThere have been a number of multiattribute decision aids developed to aid selection problems. Multiattribute value theory and the analytic hierarchy process are two commonly used techniques. Different systems can result in radically different conclusions if they inaccurately and inconsistently reflect the preference structure of decision makers, or if they are based on inappropriate theoretical models. This study examines the impact of the underlying theoretical model, the method in which preference information is elicited, and the structure of alternatives as influences on the results from using various decision aids. It was found that two systems based on the multiattribute value theory model were just as diverse in their conclusions as were results between AHP and the multiattribute value theory models. Therefore, accuracy of information reflecting decision maker preference is an important consideration. Feedback capable of assuring the decision maker that information provided is consistent is a necessary feature required of decision aids applied to selection problems. The study also found that the way in which information is elicited influenced the result more than did the underlying model. Exact numerical data for complex concepts such as attribute importance and alternative performance on attributes is not necessary, and elicitation procedures that are more natural for the user are likely to be more accurate.

ISSN:0011-7315    

DOI:10.1111/j.1540-5915.1995.tb01573.x

出版商:Blackwell Publishing Ltd    

年代:1995

数据来源: WILEY

摘要:

ABSTRACTWe present a simple scheme for the automated, iterative specification of the genetic mutation, crossover, and reproduction (usage) probabilities during run time for a specific genetic algorithm‐driven tool. The tool is intended for supporting static scheduling decisions in flexible manufacturing systems. Using a randomly generated (base) test problem instance, we first assess the method by using it to determine the appropriate levels for specific types of mutation and crossover operators. The level for the third operator, reproduction, may then be inferred. We next report on its ability to choose one or more appropriate crossovers from a set of many such operators. Finally, we compare the method's performance with that of approaches suggested in prior research for the base problem and a number of other test problems. Our experimental findings within the specific scheduling domain studied suggest that the simple method could potentially be a valuable addition to any genetic algorithmbased decision support tool. It is, therefore, worthy of additional investigation

ISSN:0011-7315    

DOI:10.1111/j.1540-5915.1995.tb01574.x

出版商:Blackwell Publishing Ltd    

年代:1995

数据来源: WILEY

摘要:

ABSTRACTA primary purpose of accounting is to provide information for decision makers. Accounting misstatements may have a detrimental effect on decision making. The Securities and Exchange Commission (SEC) identifies earnings overstatements as being particularly troublesome to users, as indicated by SEC Accounting and Auditing Enforcement Releases' emphasis on earnings' overstatement errors. This research investigates how security analysts' forecast revisions are affected by accounting earnings overstatement errors, which become known only after the analysts released their revised annual earnings forecasts. The paper investigates the clarifying role that additional information plays in analysts' revisions. The results show that analysts draw significantly different conclusions from earnings containing (unknown) overstatement errors than from accurately reported earnings. In essence, the analysts identify some of the overstatement, at least on average, by making an adjustment that effectively ignores 21 percent of the overstatement error.

ISSN:0011-7315    

DOI:10.1111/j.1540-5915.1995.tb01575.x

出版商:Blackwell Publishing Ltd    

年代:1995

数据来源: WILEY

摘要:

ABSTRACTThe widespread use of regression analysis as a business forecasting tool and renewed interest in the use of cross‐validation to aid in regression model selection make it essential that decision makers fully understand methods of cross‐validation in forecasting, along with the advantages and limitations of such analysis. Only by fully understanding the process can managers accurately interpret the important implications of statistical cross‐validation results in their determination of the robustness of regression forecasting models. Through a multiple regression analysis of a large insurance company's customer database, the Herzberg equation for determining the criterion of validity [11] and analysis of samples of different size from the two regions covered by the database, we illustrate the use of statistical cross‐validation and test a set of factors hypothesized to be related to the statistical accuracy of validation. We find that increasing sample size will increase reliability. When the magnitude of population model differences is small, validation results are found to be unreliable, and increasing sample size has little or no effect on reliability. In addition, the relative fit of the model for the derivative sample and the validation sample has an impact on validation accuracy, and should be used as an indicator of when further analysis should be undertaken. Furthermore, we find that the probability distribution of the population independent variables has no effect on validation a

ISSN:0011-7315    

DOI:10.1111/j.1540-5915.1995.tb01576.x

出版商:Blackwell Publishing Ltd    

年代:1995

数据来源: WILEY

摘要:

ABSTRACTRussell and Krajewski presented an optimal purchase order quantity algorithm that considered the effect of the transportation rate structure for less‐than‐truckload (LTL) shipments. The authors applied the Russell and Krajewski algorithm to a variety of freight classes and lengths‐of‐haul. Anomalous cases were found in which the freight rate schedule, when used with the suggested algorithm, resulted in incorrect order size decisions. In this comment, the authors consider the impact of these anomalies on the optimal order quantity and associated total costs. A procedure is presented to adjust the Russell and Krajewski algorithm to arrive at the optimal purchase order quantity and the lowest total annu

ISSN:0011-7315    

DOI:10.1111/j.1540-5915.1995.tb01577.x

出版商:Blackwell Publishing Ltd    

年代:1995

数据来源: WILEY

摘要:

ABSTRACTAnalysis of covariance (ANCOVA) integrates analysis of variance (ANOVA) and regression. The basic advantages of ANCOVA over ANOVA are: (1) generally greater power, and (2) reduction in bias caused by differences between groups that exist before experimental treatments are administered. ANCOVA has numerous possible applications in the evaluation of simulation output, especially where the values of covariates are not known until after the simulation experiment is completed. These covariates are uncontrolled experimental variables that influence the response but are themselves unaffected by the experimental factors.This paper provides an application of multiple analysis of covariance (MANCOVA) to a simulation experiment to determine whether an intermodal transfer and blending facility should add commodity handling and storage capacity. A discrete simulation model of the plant generated cash flows from several proposed capital projects. These cash flows indicated that capacity expansion was a prudent decision. However, when the treatment means for the various combinations of additional capacity were adjusted by MANCOVA for the same levels of operating volume and scheduling performance, the adjusted cash flows produced unacceptable financial returns. In this example, the increased precision of the MANCOVA model suggested that plant management should not invest in additional storage and commodity handling capacity.

ISSN:0011-7315    

DOI:10.1111/j.1540-5915.1995.tb01578.x

出版商:Blackwell Publishing Ltd    

年代:1995

数据来源: WILEY