Experiential Conjoint Analysis: An Experience Based Method for Eliciting, Capturing, and Modeling Consumer PreferenceSource: Journal of Mechanical Design:;2014:;volume( 136 ):;issue: 010::page 101404DOI: 10.1115/1.4027985Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Traditionally, consumer preference is modeled in terms of preference for the aesthetic and functional features of a product. This paper introduces a new means to model consumer preference that accounts for not only for how a product looks and functions but also how it feels to interact with it. Traditional conjointbased approaches to preference modeling require a participant to judge preference for a product based upon a static 2D visual representation or a feature list. While the aesthetic forms and functional features of a product are certainly important, the decision to buy or not to buy a product often depends on more, namely, the experience or feel of use. To address the importance of the product experience, we introduce the concept of experiential conjoint analysis, a method to mathematically capture preference for a product through experiencebased (experiential) preference judgments. Experiential preference judgments are made based upon the use, or simulated use, of a product. For many products, creating enough physical prototypes to generate a preference model is cost prohibitive. In this work, virtual reality (VR) technologies are used to allow the participant an interactive virtual product experience, provided at little investment. The results of this work show that providing additional interactionbased (interactional) information about a product through a product experience does not affect the predictive ability of the resulting preference models. This work additionally demonstrates that the preference judgments of virtual product representations are more similar to preference judgments of real products than preference judgments of 2D product representations are. When examining similarity of modeled preference, experiential conjoint is found to be superior to visual conjoint with respect to mean absolute error (MAE), but with respect to correlation no significant difference between visual and experiential is found.
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contributor author | Tovares, Noah | |
contributor author | Boatwright, Peter | |
contributor author | Cagan, Jonathan | |
date accessioned | 2017-05-09T01:10:44Z | |
date available | 2017-05-09T01:10:44Z | |
date issued | 2014 | |
identifier issn | 1050-0472 | |
identifier other | md_136_10_101404.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/155702 | |
description abstract | Traditionally, consumer preference is modeled in terms of preference for the aesthetic and functional features of a product. This paper introduces a new means to model consumer preference that accounts for not only for how a product looks and functions but also how it feels to interact with it. Traditional conjointbased approaches to preference modeling require a participant to judge preference for a product based upon a static 2D visual representation or a feature list. While the aesthetic forms and functional features of a product are certainly important, the decision to buy or not to buy a product often depends on more, namely, the experience or feel of use. To address the importance of the product experience, we introduce the concept of experiential conjoint analysis, a method to mathematically capture preference for a product through experiencebased (experiential) preference judgments. Experiential preference judgments are made based upon the use, or simulated use, of a product. For many products, creating enough physical prototypes to generate a preference model is cost prohibitive. In this work, virtual reality (VR) technologies are used to allow the participant an interactive virtual product experience, provided at little investment. The results of this work show that providing additional interactionbased (interactional) information about a product through a product experience does not affect the predictive ability of the resulting preference models. This work additionally demonstrates that the preference judgments of virtual product representations are more similar to preference judgments of real products than preference judgments of 2D product representations are. When examining similarity of modeled preference, experiential conjoint is found to be superior to visual conjoint with respect to mean absolute error (MAE), but with respect to correlation no significant difference between visual and experiential is found. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Experiential Conjoint Analysis: An Experience Based Method for Eliciting, Capturing, and Modeling Consumer Preference | |
type | Journal Paper | |
journal volume | 136 | |
journal issue | 10 | |
journal title | Journal of Mechanical Design | |
identifier doi | 10.1115/1.4027985 | |
journal fristpage | 101404 | |
journal lastpage | 101404 | |
identifier eissn | 1528-9001 | |
tree | Journal of Mechanical Design:;2014:;volume( 136 ):;issue: 010 | |
contenttype | Fulltext |