Multiattribute Preference Models Research Articles

Multiattribute preference models with reference points

In the context of multiple attribute decision making, preference models making use of reference points in an ordinal way have recently been introduced in the literature. This text proposes an axiomatic analysis of such models, with a particular emphasis on the case in which there is only one reference point. Our analysis uses a general conjoint measurement model resting on the study of traces induced on attributes by the preference relation and using conditions guaranteeing that these traces are complete. Models using reference points are shown to be a particular case of this general model. The number of reference points is linked to the number of equivalence classes distinguished by the traces. When there is only one reference point, the induced traces are quite rough, distinguishing at most two distinct equivalence classes. We study the relation between the model using a single reference point and other preference models proposed in the literature, most notably models based on concordance and models based on a discrete Sugeno integral.

Enabling e-transactions with multi-attribute preference models

This paper describes potential applications of multi-attribute preference models (MAPM) in e-commerce and offers some guidelines for their implementation. MAPM are methodologies for modeling complex preferences that depend on more than one attribute or criterion, and include multi-attribute utility theory, conjoint analysis, and the Analytic Hierarchy Process. There are numerous examples of applications in e-commerce that would benefit from the acquisition of information regarding the preferences of a consumer, a customer, an advice seeker, or a decision maker. Here, the focus is on applications of MAPM models in B2C and B2B websites, where preferences of consumers are assessed for the purpose of identifying products or services that closely match their needs. In this paper, we provide an overview of decision aids with the MAPM approach, emphasizing how the MAPM structure of an individual’s preferences may be assessed. This discussion is illustrated with examples of the use of alternative MAPM assessment approaches that are incorporated in existing websites. We then discuss how MAPM applications should be tailored for success in these environments.

Multi-attribute Services Brokering in Agent-based Virtual Private Networks

This paper presents the development of an agent-based Virtual Private Network (VPN) system that supports multimedia service brokering. The VPN agents employ multi-attribute preference models in order to represent the end-user preferences, and a multi-criteria decision making model to evaluate available services from network providers. A prototype multi-agent system demonstrating the proposed approach has also been implemented.

Comparing the predictive validity of alternatively assessed multi-attribute preference models when relevant decision attributes are missing

Multi-attribute deision problems require that trade-offs between conflicting objectives be made when evaluating choice alternatives. To overcome the shortcomings inherent in unaided intuitive decision maker evaluations, decision theorists have prescribed formal procedure to improve decision making. Such procedures elicit a descriptive model of choice for the alternatives being considered. Although these procedures are founded on thebelieed that the subject's preference are well defined and error free, psychological studies have shown that errors do arise in the elicitation process. Thus, the formal preference elicitation procedure employed should be structurally capable of encoding meaningful preferences in the presence of these response errors. This study employs a simulated decision making environment to compare the predictive validity of alternatively assessed models when relevant attributes are omitted from the elicitation process and preference responses are not error free. The study found that meaningful preference predictions are sensitive to the elicitation procedure employed.

A cross validation test of four models for quantifying multiattribute preferences

This paper examines the internal predictive validity of four multiattribute preference models: (a) a self-explicated model with equal importance weights; (b) a self-explicated model with unequal weights; (c) Sawtooth Software's Adaptive Conjoint Analysis (ACA); and (d) full profile conjoint analysis. We also discuss the problem of choosing criterion measures for comparing cross validations across models.

Decompositional Multiattribute Preference Models in Spatial Choice Analysis: A Review of Some Recent Developments

Decompositional Multiattribute Preference Models in Spatial Choice Analysis: A Review of Some Recent Developments

A Comparison of the Internal Validity of Alternative Parameter Estimation Methods in Decompositional Multiattribute Preference Models

Since 1971, interest in the use of decompositional multiattribute preference models in marketing has been increasing. The applications have varied in terms of the type of data used, behavior predicted, and methods used for estimating parameters. The authors examine the effect of different data collection and estimation procedures on parameter estimates and their stability and validity. An actual data base is used. A detailed comparison is made of the alternative approaches of parameter estimation and suggestions are given for the potential users of decompositional multiattribute preference models.