Rule-Based Expert Systems and Linear Models: An Empirical Comparison of Learning-By-Examples Methods*

Building models of expert decision-making behavior from examples of experts’ decisions continues to receive considerable research attention. In the 1960's and 70's, linear models derived by statistical methods were studied extensively. More recently, rule-based expert systems derived by induction algorithms have been the focus of attention. Few studies compare the two approaches. This paper reports on a study that compared linear models derived by logistic regression with rule-based systems produced by two induction algorithms—ID3 and the genetic algorithm. The techniques performed comparably in modeling the experts at one task, graduate admissions, but differed significantly at a second task, bidder selection.     

TALKING ABOUT PROBABILITIES: A LOGICAL PROBLEM FOR OR/MS

The 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.     

Conceptualizing Effects of Office Information Systems: A Methodology and Application for the Study of Alpha,Beta, and Gamma Changes*

This article applies the concepts of alpha, beta, and gamma changes to test whether the implementation of a new office information system with networking capabilities changes the way organizational members conceptualize office work. The traditional approach (t-test) was used to measure alpha change and indicated little change in how effectively the respondents felt they performed eight generic office activities before implementation (T1) and nine months after implementation (T2). However, considerable change was detected between effectiveness reported at T1 and a retrospective assessment of T1 effectiveness reported at T2 (called “then” assessments). Strong change was also detected between “then” assessments and T2 effectiveness reported at T2, indicating beta change. Multiple hierarchical tests showed that most of the change was actually gamma change; the T2 and the “then” factor structures and covariances differed significantly. This study supports propositions that using computers to accomplish organizational work may be associated with different conceptualizations of work, which may create ambiguity and uncertainty if training and management policies do not respond appropriately. Finally, this study provides an expanded version of a prior solution to detecting alpha, beta, and gamma changes.     

Decisional Conflict and User Acceptance of Multicriteria Decision-Making Aids*

Despite the development of increasingly sophisticated and refined multicriteria decision-making (MCDM) methods, an examination of the experimental evidence indicates that users most often prefer relatively unsophisticated methods. In this paper, we synthesize theories and empirical findings from the psychology of judgment and choice to provide a new theoretical explanation for such user preferences. Our argument centers on the assertion that the MCDM method preferred by decision makers is a function of the degree to which the method tends to introduce decisional conflict. The model we develop relates response mode, decision strategy, and the salience of decisional conflict to user preferences among decision aids. We then show that the model is consistent with empirical results in MCDM studies. Next, the role of decisional conflict in problem formulation aids is briefly discussed. Finally, we outline future research needed to thoroughly test the theoretical mechanisms we have proposed.     

AN EMPIRICAL EXAMINATION OF THE BIASING EFFECTS OF FRAMING ON BUSINESS DECISIONS*

This paper presents results of three studies testing whether decision bias due to framing, found in consumer purchase contexts, also would occur in a business setting. In the first study, business-student subjects displayed framing-induced decision bias just as subjects had in an earlier study by Tversky and Kahneman [12]. When the consumer problem was recast into a business decision in the second study, student subjects trained to handle the problem still revealed bias, although to a lesser extent. In the third study, experienced business managers revealed the same pattern of decision bias as the student subjects. Implications of this bias for business decision makers are discussed.     

Planning Forward by Looking Backward: Retrospective Thinking in Strategic Decision Making*

Retrospective thinking occurs whenever one remembers something from the past, but one can also think retrospectively about hypothetical future events, by imagining that the event has already transpired and then working backward in the mind from the future toward the present. Designers, artists, planners, and other creative individuals utilize retrospective thinking when they mentally envision the object they wish to create and then thinkabout how it might be constructed. Some theorists and some previous research have suggested that forward and backward thinking are different cognitive processes, but there has been little investigation on the nature of these differences. This article examines the literature and describes a laboratory study designed to investigate retrospective thinking as a technique for increased idea generation. Subjects (n=64) were professional planners and managers with an average business experience of over 20 years. In a planning task, significantly more ideas were generated in the retrospective thinking mode than in the prospective mode, but the ideas were not found to be of greater quality. Evidence emerged that a subset of subjects were better able to make use of the retrospective technique, suggesting that selection along with training may be appropriate for the technique's mosteffective use.     

Examining Pathways from Innovation Orientation to Patient Satisfaction: A Relational View of Healthcare Delivery*

The federal government and industry leaders view innovation as a potentially fruitful way to improve hospital performance, specifically patient satisfaction. However, translating a hospital's innovation orientation into improved performance is challenging given that important network participants—namely physicians—may possess different aims. Grounded in Relational RBV, this study tests a model linking innovation orientation to patient satisfaction through a pathway of knowledge‐sharing routines (physician partnering and customer relationship management) and complementary capabilities (hospital responsiveness). Further, this study investigates the moderating role of physician employment (a form of governance) by examining hospitals with high and low levels of employed physicians. Structural Equation Modeling results from a paired sample of primary survey and secondary data from 173 acute care hospitals in the USA reveal the following. Hospitals with high levels of employed physicians translate innovation orientation into patient satisfaction by using customer relationship management (CRM) programs to influence hospital responsiveness directly, ultimately leading to patient satisfaction. Hospitals with low levels of physician employment use CRM programs in a fully mediated fashion to inform physician partnering activities, which influence hospital responsiveness, driving patient satisfaction.     

Multiple Attribute Decision Making with Inexact Value-Function Assessment

A major issue in value-function assessment is the possibility of receiving an indefinite response from a decision maker to a question about preferences. The conventional treatment requires a single, definite response from the decision maker. This approach either assumes that response error is zero or accepts the final solution as only approximate, without knowing how approximate it might be. In this paper we examine the issue of indefinite responses, define it more precisely, and present a method for incorporating it into decision making. The method is adaptive in that it is iterative and interactive with the decision maker who, at each iteration, is provided with information regarding the potential advantage of answering more trade-off questions and/or answering questions more carefully to reduce response error. In contrast to other approaches that “force” rationality and decisiveness, we work with irrationality and indecisiveness on the part of the decision maker. The method is demonstrated for the case of concave, increasing value functions.     

A COMPARISON OF UNIT,SUBJECTIVE, AND REGRESSION MEASURES OF SECOND-LEVEL VALENCES IN EXPECTANCY THEORY

Two different decision-making exercises are compared with unit weights and with traditional Likert scales as measures of second-level valences in expectancy theory. Second-level valences are measured across different levels of outcomes in each exercise and compared to the traditional subjective- and unit-weight measures. In the first experiment, the job-preference decisions of 21 undergraduates are examined using a decision-making exercise involving 24 hypothetical jobs described in terms of three intrinsic instrumentalities at two levels. In the second experiment, a different 21 undergraduates make job-preference decisions in a decision-making exercise involving 27 hypothetical jobs described in terms of three extrinsic instrumentalities at three levels. The β-weight (standardized regression coefficient) measures of the second-level valences are found to be more powerful predictors of job-preference decisions than either subjective-weight or unit-weight measures, both before and after shrinkage. They also had higher cross validations, exhibited higher test-retest reliability, and allowed testing of a quadratic motivational effect in the three-level exercise.     

DUAL-METRIC MEASUREMENT OF THE IMPACT OF COMPLEXITY ON DECISION QUALITY*

Both sophisticated and unsophisticated subjects were provided either a simple or a complex cue set at random on which to base decisions. A dual-metric approach that consisted of measuring interrater consistency and cross-item variance for each subject category was used to compare the decision quality of the subjects. Although complexity and decision quality were inversely related, the sophisticated subjects performed relatively better using the complex cue set; the unsophisticated subjects performed better using the simple cue set. These findings support the notion that decision-maker and task compatibility are important to the assessment of decision quality.