Publication Type
Journal Article
Version
publishedVersion
Publication Date
9-2017
Abstract
A critical task in product design is mapping information from consumer to design space. Currently, this process largely depends on designers identifying and mapping psychological and consumer level factors to engineered attributes. In this way, current methodologies lack provision to test a designer's cognitive reasoning and could introduce bias when mapping from consumer to design space. In addition, current dominant frameworks do not include user-product interaction data in design decision making, nor do they assist designers in understanding why a consumer has a particular perception about a product. This paper proposes a framework-cyber-empathic (CE) design-where user-product interaction data are acquired using embedded sensors. To gain insight into consumer perceptions relative to product features, a network of psychological constructs is utilized. Structural equation modeling (SEM) is used as the parameter estimation and hypothesis testing technique, making the framework falsifiable in nature. To demonstrate effectiveness of the framework, a case study of sensor-integrated shoes is presented, where two models are compared-one survey-only and one using the cyber-empathic framework model. Covariance-based SEM (CB-SEM) is used to estimate the parameters and the fit indices. It is shown that the cyber-empathic framework results in improved fit over a survey-only SEM. This work demonstrates how low-level user-product interaction data can be used to understand and model user perceptions in a way that can support falsifiable design inference.
Keywords
cyber-empathic design, data-driven design, design methodology, product design, product development
Discipline
Marketing | Technology and Innovation
Research Areas
Marketing
Publication
Journal of Mechanical Design
Volume
139
Issue
9
First Page
1
Last Page
12
ISSN
1050-0472
Identifier
10.1115/1.4036780
Publisher
American Society of Mechanical Engineers (ASME)
Citation
GHOSH, Dipanjan; OLEWNIK, Andrew; LEWIS, Kemper; KIM, Junghan; and LAKSHAMAN, Arun.
Cyber-Empathic Design: A data-driven framework for product design. (2017). Journal of Mechanical Design. 139, (9), 1-12.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/5316
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1115/1.4036780