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Human Judgment (human + judgment)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	55%

Selected Abstracts

Human judgments in New York state sales and use tax forecasting

JOURNAL OF FORECASTING, Issue 4 2004
Yu-Ying Kuo
Abstract Human judgments have become quite important in revenue forecasting processes. This paper centres on human judgments in New York state sales and use tax by examining the actual practices of information integration. Based on the social judgment theory (i.e., the lens model), a judgment analysis exercise was designed and administered to a person from each agency (the Division of the Budget, Assembly Ways and Means Committee Majority and Minority, and the Senate Finance Committee) to understand how information integration is processed among different agencies. The results of the judgment analysis exercise indicated that revenue forecasters put different weight on cues. And, in terms of relative and subjective weights, the cues were used differently, although they were presented with the same information. Copyright © 2004 John Wiley & Sons, Ltd. [source]

'Everything is relative': Comparison processes in social judgment The 2002 Jaspars Lecture

EUROPEAN JOURNAL OF SOCIAL PSYCHOLOGY, Issue 6 2003
Thomas Mussweiler
Any judgment involves a comparison of the evaluated target to a pertinent norm or standard, so that comparison processes lie at the core of human judgment. Despite this prominent role, however, little is known about the psychological mechanisms that underlie comparisons and produce their variable consequences. To understand these consequences, one has to examine what target knowledge is sought and activated during the comparison process. Two alternative comparison mechanisms are distinguished. Similarity testing involves a selective search for evidence indicating that the target is similar to the standard and leads to assimilation. Dissimilarity testing involves a selective search for evidence indicating that the target is dissimilar from the standard and leads to contrast. Distinguishing between these alternative mechanisms provides an integrative perspective on comparison consequences in the realm of social comparison and beyond. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Off-site monitoring systems for predicting bank underperformance: a comparison of neural networks, discriminant analysis, and professional human judgment

INTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 3 2001
Philip Swicegood
This study compares the ability of discriminant analysis, neural networks, and professional human judgment methodologies in predicting commercial bank underperformance. Experience from the banking crisis of the 1980s and early 1990s suggest that improved prediction models are needed for helping prevent bank failures and promoting economic stability. Our research seeks to address this issue by exploring new prediction model techniques and comparing them to existing approaches. When comparing the predictive ability of all three models, the neural network model shows slightly better predictive ability than that of the regulators. Both the neural network model and regulators significantly outperform the benchmark discriminant analysis model's accuracy. These findings suggest that neural networks show promise as an off-site surveillance methodology. Factoring in the relative costs of the different types of misclassifications from each model also indicates that neural network models are better predictors, particularly when weighting Type I errors more heavily. Further research with neural networks in this field should yield workable models that greatly enhance the ability of regulators and bankers to identify and address weaknesses in banks before they approach failure. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Multicriteria group decision making under incomplete preference judgments: Using fuzzy logic with a linguistic quantifier

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 6 2007
Duke Hyun Choi
In the face of increasing global competition and complexity of the socioeconomic environment, many organizations employ groups in decision making. Inexact or vague preferences have been discussed in the decision-making literature with a view to relaxing the burden of preference specifications imposed on the decision makers and thus taking into account the vagueness of human judgment. In this article, we present a multiperson decision-making method using fuzzy logic with a linguistic quantifier when each group member specifies incomplete judgment possibly both in terms of the evaluation of the performance of different alternatives with respect to multiple criteria and on the criteria themselves. Allowing for incomplete judgment in the model, however, makes a clear selection of the best alternative by the group more difficult. So, further interactions with the decision makers may proceed to the extent to compensate for the initial comfort of preference specifications. These interactions, however, may not guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfactory solution by the use of a linguistic-quantifier-guided aggregation that implies the fuzzy majority. This is an approach that combines a prescriptive decision method via mathematical programming and a well-established approximate solution method to aggregate multiple objects. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 641,660, 2007. [source]

Determining the importance weights for the design requirements in the house of quality using the fuzzy analytic network approach

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 5 2004
Gülçin Büyüközkan
Quality function deployment (QFD) has been used to translate customer needs (CNs) and wants into technical design requirements (DRs) in order to increase customer satisfaction. QFD uses the house of quality (HOQ), which is a matrix providing a conceptual map for the design process, as a construct for understanding CNs and establishing priorities of DRs to satisfy them. This article uses the analytic network process (ANP), the general form of the analytic hierarchy process (AHP), to prioritize DRs by taking into account the degree of the interdependence between the CNs and DRs and the inner dependence among them. In addition, because human judgment on the importance of requirements is always imprecise and vague, this work concentrates on a fuzzy ANP approach in which triangular fuzzy numbers are used to improve the quality of the responsiveness to CNs and DRs. A numerical example is presented to show the proposed methodology. © 2004 Wiley Periodicals, Inc. [source]

In defense of clinical judgment , and mechanical prediction

JOURNAL OF BEHAVIORAL DECISION MAKING, Issue 5 2006
Jason Dana
Abstract Despite over 50 years of one-sided research favoring formal prediction rules over human judgment, the "clinical-statistical controversy," as it has come to be known, remains something of a hot-button issue. Surveying the objections to the formal approach, it seems the strongest point of disagreement is that clinical expertise can be replaced by statistics. We review and expand upon an unfortunately obscured part of Meehl's book to try to reconcile the issue. Building on Meehl, we argue that the clinician provides information that cannot be captured in, or outperformed by, mere frequency tables. However, that information is still best harnessed by a mechanical prediction rule that makes the ultimate decision. Two original studies support our arguments. The first study shows that multivariate prediction models using no data other than clinical speculations can perform well against statistical regression models. Study 2, however, showed that holistic predictions were less accurate than predictions made by mechanically combining smaller judgments without input from the judge at the combination stage. While we agree that clinical expertise cannot be replaced or neglected, we see no ethical reason to resist using explicit, mechanical rules for socially important decisions. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Commentary: A Response to Reckase's Conceptual Framework and Examples for Evaluating Standard Setting Methods

EDUCATIONAL MEASUREMENT: ISSUES AND PRACTICE, Issue 3 2006
E. Matthew Schulz
A look at real data shows that Reckase's psychometric theory for standard setting is not applicable to bookmark and that his simulations cannot explain actual differences between methods. It is suggested that exclusively test-centered, criterion-referenced approaches are too idealized and that a psychophysics paradigm and a theory of group behavior could be more useful in thinking about the standard setting process. In this view, item mapping methods such as bookmark are reasonable adaptations to fundamental limitations in human judgments of item difficulty. They make item ratings unnecessary and have unique potential for integrating external validity data and student performance data more fully into the standard setting process. [source]