Massachusetts Institute of Technology
Design for surprise and idea generation methods
Abstract
dc:description.abstractThis thesis explores the meaning of surprise in product design and how surprise can be created in the early phase of the design process, specifically during ideation. In product and service markets with multiple competitors and where product differentiation is difficult, surprise, if used correctly, can be an indispensable differentiator-creating emotional attachment and fostering brand loyalty. A two-part experiment tests three different idea generation methods-brainstorming, multiple perspectives, and counter attributes (a new method proposed in this thesis)-and how ideation sketches from these methods are rated by workers on Amazon's Mechanical Turk. Findings reveal that counter attributes may be less effective at generating surprising ideas. Brainstorming and multiple perspectives perform similarly to each other, but small differences in the structure of an idea generation method may either inhibit or encourage creativity and surprise. The findings also reveal that how clearly an idea is expressed in a sketch greatly influences the variance for how it will be rated upon review.
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2011
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Tsai, Geoffrey T
- Advisor dc:contributor.advisor
-
- Maria C. Yang.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/67804
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/67804