In:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting, SAGE Publications, Vol. 59, No. 1 ( 2015-09), p. 448-452
Abstract:
The intent of this paper is to advance the use of structural equation modeling (SEM) in user experience research, adding another tool to the user experience toolkit. The resulting models help communicate the value of user experience research to business stakeholders and decision makers. SEM is a confirmatory modeling technique that allows practitioners to specify and test relationships of latent (unobserved) and manifest (observed) variables. To this end, two SEM case studies are described, where the observed variables were users’ responses and experiences with product features hypothesized to impact system usability, customer satisfaction, and customer loyalty. The models were used to identify actionable items that can lead to measurable improvements in customer experience. SEM is recommended over other modeling methods for its ability to condense large datasets into a few, theory-driven dimensions, its direct modeling of variable covariances, and its missing data management.
Type of Medium:
Online Resource
ISSN:
2169-5067
,
1071-1813
DOI:
10.1177/1541931215591095
Language:
English
Publisher:
SAGE Publications
Publication Date:
2015
detail.hit.zdb_id:
2415770-3
