User-Experience from an Inference Perspective

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User-Experience from an Inference Perspective PAUL VAN SCHAIK, Teesside University MARC HASSENZAHL, Folkwang University JONATHAN LING, University of Sunderland

In many situations, people make judgments on the basis of incomplete information, inferring unavailable attributes from available ones. These inference processes may also well operate when judgments about a product’s user-experience are made. To examine this, an inference model of user-experience, based on Hassenzahl and Monk’s [2010], was explored in three studies using Web sites. All studies supported the model’s predictions and its stability, with hands-on experience, different products, and different usage modes (action mode versus goal mode). Within a unified framework of judgment as inference [Kruglanski et al. 2007], our approach allows for the integration of the effects of a wide range of information sources on judgments of user-experience. Categories and Subject Descriptors: H.1.2 [Models and Principles]: User/Machine Systems—Human information processing; H.5.2 [Information Interfaces and Presentation]: User Interfaces—Theory and methods; H.5.4 [Information Interfaces and Presentation]: Hypertext/Hypermedia—Theory; I.6.5 [Simulation and Modeling]: Model Development General Terms: Experimentation, Human Factors, Theory Additional Key Words and Phrases: User-experience, model, inference perspective, beauty, aesthetics ACM Reference Format: van Schaik, P., Hassenzahl, M., and Ling, J. 2012. User-experience from an inference perspective. ACM Trans. Comput.-Hum. Interact. 19, 2, Article 11 (July 2012), 25 pages. DOI = 10.1145/2240156.2240159 http://doi.acm.org/10.1145/2240156.2240159

1. INTRODUCTION

Imagine you want to enhance your voice-over-IP-calls with a high-definition image. By coincidence, a local shop makes an exceptional offer (in terms of “value for money”) of a multifunctional (“all-singing-all-dancing”) webcam. Will you accept? The problem is to predict whether or to what extent the product would meet your needs. As you have no hands-on experience, you visit the shop to see for yourself what the product looks like in reality and to get further information from the helpful staff. However, you are not allowed to open the attractive transparent box in which the seductive product patiently awaits your expenditure. You simply cannot try the product before buying it. Therefore, in effect, you try to “guess”—or infer—the product’s reliability, usefulness and ease of use from the specific pieces of information that you find relevant. This type of inference is a ubiquitous process, which underlies many phenomena [Kardes et al. 2004b; Loken 2006]; some even argue that it is the very essence of Authors’ addresses: P. van Schaik, School of Social Sciences and Law, Teesside University, United Kingdom; email: p.van-schaik@tees.ac.uk; M. Hassenzahl, Ergonomics in Industrial Design, Folkwang University, Germany; J. Ling, Faculty of Applied Sciences, University of Sunderland. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from the Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701, USA, fax +1 (212) 869-0481, or permissions@acm.org. c 2012 ACM 1073-0516/2012/07-ART11 $15.00 DOI 10.1145/2240156.2240159 http://doi.acm.org/10.1145/2240156.2240159

ACM Transactions on Computer-Human Interaction, Vol. 19, No. 2, Article 11, Publication date: July 2012.

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