The Effectiveness of Partial Information about Attribute Weights for Ranking Alternatives in Multiattribute Decision Making

Weighted additive evaluation functions are widely used to rank alternatives in decision making under certainty with multiple evaluation attributes. Some researchers have suggested that approximate attribute weights may be adequate to accurately rank alternatives. Use of approximate weights would simplify decision analysis since detailed elicitation of weights can be time consuming and controversial. This article investigates the degree to which partial information about the relative magnitudes of attribute weights is sufficient to rank alternatives as a function of the number of decision alternatives, the number of attributes, and the number of allowed levels for each attribute. A simulation analysis, as well as a reanalysis of an actual application, shows that partial information about weights is often not sufficient to determine the most preferred alternative for realistic decision problems. Hence, approximation procedures for specifying weights may lead to errors. However, our work also shows that a simple analysis procedure can be used to accurately determine whether partial information about weights is adequate to correctly specify the most preferred alternative. This procedure can be useful for identifying situations in which detailed elicitation of weights is not needed.     

Social desirability response bias as one source of the discrepancy between subjective weights and regression weights

This study of the judgment process investigated whether social desirability response bias is more closely associated with directly weighted subjective weights than less directly assessed regression weights. Graduating college students indicated their preferences for 11 job characteristics in four different tasks: (a) a statistical weighting task completed honestly, (b) a statistical weighting task completed to “look good” to a recruiter, (c) a subjective weighting task completed honestly, and (d) a subjective weighting task completed to “look good” to a recruiter. Predicted judgments were calculated from the weights obtained in each condition. Pearson correlation coefficients using these predicted judgments were computed between conditions; the relationship between the honest and positive impression predicted judgments derived from subjective weights was significantly greater than the relationship between honest and positive impression predicted judgments derived from regression weights for 19 of 23 participants. It was concluded that social desirability response bias was more closely related to subjective weights than to regression Weights.     

Interpersonal trust and market value moderates the bias in women’s preferences away from attractive high-status men

Women appear to exhibit a subtle reluctance to engage in long-term relationships with physically attractive, high-status men. We propose that this bias away from men of very high market value is based on fear that these males may desert a relationship and also on the comparative self-perceived market value of the women. Therefore, interpersonal trust and perceived market value should moderate the extent of this counterintuitive bias. To test this proposal, we asked women with varying levels of interpersonal trust and self-perceived desirability to consider physically-attractive and physically-average men of high, medium and low socioeconomic status and rate each in terms of attractiveness as a long-term partner. Results showed that women’s perceptions of their own desirability and their level of trust predicted their ratings of men with high-value in the mating market, and that women with high levels of both desirability and trust were less likely to show a bias away from high-value men. Interpersonal trust and desirability moderate the degree to which women find physically attractive men attractive as potential partners.     

An Interactive Approach for Multicriteria Decision Making Using a Tchebycheff Utility Function Approximation

Multicriteria decision making (MCDM) can provide an efficient mean for considering various and conflicting objectives to reveal the alternative that maximizes the decision maker's (DM) utility. In this paper, we propose a new interactive MCDM method for implicit alternatives to help a DM obtain a most preferred solution. We employ a Tchebycheff function to generate weights for objectives consistent with the DM's responses to pairwise comparisons between alternatives and present a mixed integer linear programming formulation to generate these weights. Thus, we approximate the DM's utility function by a Tchebycheff function and generate weights consistent with the DM's responses. We test our approach with different true utility functions on various sized multiple criteria linear programming problems. The computational results show that even with non‐Tchebycheff true utility functions, our method can generate alternatives very close to the optimal solution with few questions. The comparison of our results with other methods reveals its advantages. Copyright © 2013 John Wiley & Sons, Ltd.     

Effects of choice task on attribute memory

Winnowing process models of multiattribute choice in which alternatives are successively eliminated in stages based on partial information predict differential memory for minor attributes as a function of an alternative's relative desirability. This prediction, which differs from the results of judgment studies finding little or no relationship between evaluation and memory, was tested in two experiments in which the choice task (Choose 1 vs Choose 3) and the density of the option set were varied. Better memory for minor attributes of relatively desirable alternatives was observed for those conditions requiring the more difficult decisions, namely the Choose 1 task with a dense set of good alternatives. A third experiment replicated these results and demonstrated that the minor attributes did influence choice. The results of all three experiments are generally consistent with winnowing models. However, detailed analysis of the memory data revealed that only attributes of the chosen alternative were remembered better; this is not entirely consistent with those models. Implications of these results for models of memory and choice are discussed.     

Item Desirability Effects in Compliance-Gaining Research Seven Studies Documenting Artifacts in the Strategy Selection Procedure

A popular method for assessing compliance-gaming behavior involves having people rate lists of preformulated message strategies for likelihood of use. This “selection procedure” has been employed much more frequently than the alternative “construction procedure,” a method that requires people to generate their own message strategies. The present article argues that the selection procedure is much less sensitive than the construction procedure to the effects of situational and individual-difference variables on compliance-gaining behavior. The article further suggests that the insensitivity of the selection procedure is due to a type of social desirability bias known as the item desirability effect. Seven studies were carried out testing the Marwell and Schmitt (1967) and Wiseman and Schenk-Hamlin (1 981) strategy checklists for the item desirability effect. These studies found that (a) the likelihood of use ratings prouided for the strategies on both checklists could be accurately predicted by the rated social appropriateness of the strategies, (b) likelihood of use ratingsfor preforrnulated strategies haue relatively poor reliability, and (c) the construction procedure is much less susceptible to social desirability biases than the selection procedure. On the basis of these and related findings, it is recommended that researchers eschew the use of strategy checklists in future research.     

Wishful Thinking about the Future: Does Desire Impact Optimism?

The notion that desire for an outcome inflates optimism about that outcome has been dubbed the desirability bias or wishful thinking. In this paper, we discuss the importance of distinguishing wishful thinking from the more general concept of motivated reasoning, and we explain why documenting overoptimism or correlations between preferences and optimism is not sufficient to infer a desirability bias. Then, we discuss results from a review and meta-analysis of the experimental literature on wishful thinking. These findings, in conjunction with more recent work, not only highlight important moderators and mediators of the desirability bias but also point out limitations of the empirical research on the bias. These results also reveal an important difference between how likelihood judgments and discrete outcome predictions respond to desirability of outcomes. We conclude by presenting avenues for future research useful for understanding wishful thinking's manifestation in everyday environments and its integration with related phenomena.     

Six of One, Half Dozen of the Other: Expanding and Contracting Numerical Dimensions Produces Preference Reversals

ABSTRACT— The scales used to describe the attributes of different choice options are usually open to alternative expressions, such as inches versus feet or minutes versus hours. More generally, a ratio scale can be multiplied by an arbitrary factor (e.g., 12) while preserving all of the information it conveys about different choice alternatives. We propose that expanded scales (e.g., price per year) lead decision makers to discriminate between choice options more than do contracted scales (e.g., price per month) because they exaggerate the difference between options on the expanded attribute. Two studies show that simply increasing the size of an attribute's scale systematically changes its weight in both multiattribute preferences and willingness to pay: Expanding scales for one attribute shifts preferences to alternatives favored on that attribute.     

Inferring latent class lexicographic rules from choice data

A lexicographic rule orders multi-attribute alternatives in the same way as a dictionary orders words. Although no utility function can represent lexicographic preference over continuous, real-valued attributes, a constrained linear model suffices for representing such preferences over discrete attributes. We present an algorithm for inferring lexicographic structures from choice data. The primary difficulty in using such data is that it is seldom possible to obtain sufficient information to estimate individual-level preference functions. Instead, one needs to pool the data across latent clusters of individuals. We propose a method that identifies latent clusters of subjects, and estimates a lexicographic rule for each cluster. We describe an application of the method using data collected by a manufacturer of television sets. We compare the predictions of the model with those obtained from a finite-mixture, multinomial-logit model.     

Level of Perceptual Development and Psychosomatic Illness

The Trait Evaluation Index supposedly controls for social desirability of the alternatives in each triad by using forced-choice methodology. This claim was tested using 63 Ss asked to select the most desirable alternative in each triad. With a significant Chi-Square for an item interpreted as lack of control for desirability, 77% of the items yielded significant Chi-Squares.     

Solutions to some problems in the implementation of conjoint analysis

Methodological problems encountered in implementing conjoint analysis include (1) the impractically large set of multiattribute choice alternatives created by the factorial combination of more than a few attributes, (2) the hypothetical nature of the alternatives in the choice set, and (3) the assumption that each individual’s preferences can be described by the same composition rule. The techniques of tailoring, belief matching, and axiom testing are suggested as solutions to these problems, and their use is demonstrated in a conjoint analysis study of individuals’ contraceptive preferences. It is noted that tailoring and belief matching can also be used as methodological enhancements in functional measurement studies.     

Stating Preference for the Ethereal but Choosing the Concrete: How the Tangibility of Attributes Affects Attribute Weighting in Value Elicitation and Choice

Marketers routinely make use of stated consumer preferences and the relative attribute‐importance weights implied by these preferences when making decisions on issues such as advertising messages and product design. Using this information as a basis for managerial decision making is risky, though, if stated preferences diverge from actual choices. Practical evidence that such a divergence is of concern is provided by the current trend toward the use of stated choice‐based conjoint analysis. This article examines differences between the attribute‐importance weights consumers use during value elicitation and the attribute weights revealed to influence actual choice. The results of an empirical analysis of automobile stated preference and purchase decisions, and an experiment and subsequent qualitative analysis of wine choice, converge to suggest that consumers’ attribute weightings differ in value elicitation versus choice in a reliable manner. Specifically, we demonstrate a tangibility effect—the tendency for tangible attributes to be weighted relatively more heavily than intangible attributes in choice as compared to in value elicitation. The process underlying the tangibility effect is discussed, as are the implications for researchers and managers.     

The Impact of Alternatives to Settlement in Dyadic Negotiation

This study examines how differential power among negotiators (in the form of alternatives available to the individuals if the parties fail to reach a negotiated settlement) influences the parameters (e.g., the aspiration levels and reservation prices), the process, and the outcome of the negotiation. The results suggest that (a) the possession of an alternative increases one′s own outcome as well as joint outcome; (b) the more attractive or valuable the alternative, the greater the benefits regarding own and joint outcome; and (c) the better one′s own alternative relative to the other parties′ alternative, the larger one′s piece of the resource pie (i.e., one′s benefit increases).     

Using the Internet to investigate consumer choice spaces

Traditional investigations of consumer choice processes include a matrix of alternatives described by attributes. The researcher-createdmatrix presents a product option space for the participant. In this article, we propose an alternative methodological approach to consumer choice processes. Specifically, we investigate choice processes when a participant creates his/her own product space. We describe a Web-based program and methodology used to collect data for three customizable products. Empirical results indicate that consumers are willing and able to make choices from their own product space. This research provides a new avenue for exploring choice processes.     

Do Ranks Suffice? A Comparison of Alternative Weighting Approaches in Value Elicitation

We compared both attribute weights and overall evaluations for students′ preferences among apartments described to them in terms of nine independent attributes. Methods used for eliciting attribute weights were (a) 7-point scales; (b) value hierarchy; (c) swing weights; and two methods using importance rankings only: (d) rank order centroid and (e) rank sum weights. Multiple linear regression was also used to infer attribute weights. Test–retest reliability of overall evaluations was found to be modest. Evaluation models based on all five weight elicitation methods were superior to an equal weights model, with rank order centroid weights modestly superior to other methods.     

Attribute‐based differentiation of alternatives

An intermediate step is introduced to the dialogue decision process for decision analysis. Alternatives are refined after they have been generated within a strategy table but before they are subject to more detailed evaluation. Two or more judges create a subjective mapping from alternatives to attributes that will later be mapped to criteria. In strategy tables, each of the alternative strategies consists of a coherent set of choices made across several decisions that are to be coordinated. These strategic alternatives are modified so as to increase their differentiation in the attribute space, rather than in the decision space alone. When criteria weights are unknown, the best alternative from the modified set may be superior to the best alternative from the original set. Furthermore, analysis of the resulting alternatives may yield a better mapping of the value response surface for the action space, in the sense that this mapping leads to eventual construction of a higher value alternative. Results are reported for a consulting engagement incorporating the proposed step. Copyright © 2003 John Wiley & Sons, Ltd.     

Methods of coping with social desirability bias: A review

Social desirability is one of the most common sources of bias affecting the validity of experimental and survey research findings. From a self-presentational perspective, social desirability can be regarded as the resultant of two separate factors: self-deception and other-deception. Two main modes of coping with social desirability bias are distinguished. The first mode comprises two methods aimed at the detection and measurement of social desirability bias: the use of social desirability scales, and the rating of item desirability. A second category comprises seven methods to prevent or reduce social desirability bias, including the use of forced-choice items, the randomized response technique, the bogus pipeline, self-administration of the questionnaire, the selection of interviewers, and the use of proxy subjects. Not one method was found to excel completely and under all conditions in coping with both other-deceptive and self-deceptive social desirability bias. A combination of prevention and detection methods offers the best choice available.     

R&D Project Selection: A Decision Process Approach

The fundamental decision problem of an R&D firm is to select projects in which to invest. Most reported models dealing with this subject use sophisticated mathematical models maximizing specific attributes of the projects without dealing with the underlying motivation of the decision maker. This paper summarizes a successful application of a decision-making process involving multicriteria in the selection of R&D projects in the Ecogen Israel Partnership. We emphasize the structure of the decision problem, with the main goal of helping the decision maker to better understand the nature of his problem. We systematically generate the objective hierarchy of the decision maker, including his main criteria, subcriteria attributes and alternatives. The ‘best’ alternative can then be found using most interactive procedures found in the literature. As the decision maker is totally involved in the entire decision-making process he is better able to understand his problem and preferences.     

The role of egocentrism and focalism in the emotion intensity bias

People sometimes judge their emotions, preferences, and attitudes to be more intense than those of other people. Two experiments tested whether this emotion intensity bias in direct comparisons results from two non-motivated cognitive processes—egocentrism and focalism. In Study 1, the intensity bias was found even when comparing a friend’s preferences to peers. In Study 2, attention given to own versus other’s preferences, and the referent of the comparison (self or others) were manipulated. Results indicated that attention to others reduced the bias, presumably by reducing egocentrism. Consistent with focalism, the bias also emerged when a friend was the target of comparison, and the bias was eliminated when the self was the referent rather than the target of comparison. In the discussion, we evaluate these accounts in light of some alternative explanations for the intensity bias.