Multivariate Analysis of Consumer Preference Structures Across Multiple Categories

Author(s):  
Sri Devi Duvvuri
2013 ◽  
Vol 21 (3) ◽  
pp. 223-233
Author(s):  
Eliza Niewiadomska ◽  
Adam Grabowski

Summary In the article the formal characterization of preference spaces [1] is given. As the preference relation is one of the very basic notions of mathematical economics [9], it prepares some ground for a more thorough formalization of consumer theory (although some work has already been done - see [17]). There was an attempt to formalize similar results in Mizar, but this work seems still unfinished [18]. There are many approaches to preferences in literature. We modelled them in a rather illustrative way (similar structures were considered in [8]): either the consumer (strictly) prefers an alternative, or they are of equal interest; he/she could also have no opinion of the choice. Then our structures are based on three relations on the (arbitrary, not necessarily finite) set of alternatives. The completeness property can however also be modelled, although we rather follow [2] which is more general [12]. Additionally we assume all three relations are disjoint and their set-theoretic union gives a whole universe of alternatives. We constructed some positive and negative examples of preference structures; the main aim of the article however is to give the characterization of consumer preference structures in terms of a binary relation, called characteristic relation [10], and to show the way the corresponding structure can be obtained only using this relation. Finally, we show the connection between tournament and total spaces and usual properties of the ordering relations.


2014 ◽  
Vol 21 (2) ◽  
pp. 203-210 ◽  
Author(s):  
Björn Frank ◽  
Gulimire Abulaiti ◽  
Takao Enkawa

2005 ◽  
Vol 42 (1) ◽  
pp. 67-82 ◽  
Author(s):  
Min Ding ◽  
Rajdeep Grewal ◽  
John Liechty

Because most conjoint studies are conducted in hypothetical situations with no consumption consequences for the participants, the extent to which the studies are able to uncover “true” consumer preference structures is questionable. Experimental economics literature, with its emphasis on incentive alignment and hypothetical bias, suggests that more realistic incentive-aligned studies result in stronger out-of-sample predictive performance of actual purchase behaviors and provide better estimates of consumer preference structures than do hypothetical studies. To test this hypothesis, the authors design an experiment with conventional (hypothetical) conditions and parallel incentive-aligned counterparts. Using Chinese dinner specials as the context, the authors conduct a field experiment in a Chinese restaurant during dinnertime. The results provide strong evidence in favor of incentive-aligned choice conjoint analysis, in that incentive-aligned choice conjoint outperforms hypothetical choice conjoint in out-of-sample predictions. To determine the robustness of the results, the authors conduct a second study that uses snacks as the context and considers only the choice treatments. This study confirms the results by providing strong evidence in favor of incentive-aligned choice analysis in out-of-sample predictions. The results provide a strong motivation for conjoint practitioners to consider conducting studies in realistic settings using incentive structures that require participants to “live with” their decisions.


2001 ◽  
Vol 12 (4) ◽  
pp. 269-279 ◽  
Author(s):  
P. Bárcenas ◽  
R. Pérez de San Román ◽  
F.J. Pérez Elortondo ◽  
M. Albisu

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.


2006 ◽  
Vol 175 (4S) ◽  
pp. 385-386
Author(s):  
Tomasz M. Beer ◽  
Bryan H. Goldman ◽  
Catherine M. Tangen ◽  
Lisa B. Bland ◽  
Maha Hussain ◽  
...  

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