Optimising sensory product qualities is a priority for automotive manufacturers when developing human-machine interfaces, as user experience frameworks consider sensory aesthetics to be a main influencing factor of the overall judgement of product appeal. This empirical study examines whether users' overall judgements of product appeal can be predicted from measures of non-visual aesthetic qualities. Ninety-one UK owners of Supermini segment cars assessed five examples of rotary temperature dials. Factor analysis gave four clear factors common across all samples, of which 'unrefined loudness' and 'positivity/precision' predicted up to 26% variance in the hedonic score; both factors were similarly important in the regression models. Significant differences in appeal were observed between the samples; however, there were no effects due to age or gender. Practitioner Summary: The research shows that the overall appeal of automotive rotary dials is partially predicted by their non-visual aesthetics. These findings are applicable to the design of any products where improving the user experience is a goal, as it demonstrates that user experience models are applicable to product domains other than computing and information technology.

Download full-text PDF

Source
http://dx.doi.org/10.1080/00140139.2012.708057DOI Listing

Publication Analysis

Top Keywords

user experience
12
automotive rotary
8
rotary dials
8
product appeal
8
characterising experience
4
experience interaction
4
interaction evaluation
4
evaluation automotive
4
dials optimising
4
optimising sensory
4

Similar Publications

While telegenetic counseling has increased substantially since the start of the COVID-19 pandemic, previous studies reported concerns around building rapport, nonverbal communication, and the patient-counselor relationship. This qualitative evaluation elicited feedback from genetic counselors, referring clinicians, and patients from a single healthcare organization to understand the user-driven reasons for overall satisfaction and experience. We conducted 22 in-depth, semi-structured interviews with participants from all 3 groups between February 2022 and February 2023.

View Article and Find Full Text PDF

This paper presents the findings from a survey on factors influencing the adoption of agricultural Decision Support Systems (DSS). Our study focuses on examining the influence of behavioural, socioeconomic and farm specific characteristics on DSS adoption. Using two structural equation models, we investigate how these factors influence the willingness to pay (WTP) and willingness to adopt.

View Article and Find Full Text PDF

Background: The rapidly evolving nature of eHealth necessitates regular optimization and subsequent evaluation. Within the Dutch sexual health intervention Sense.info, we utilized a mixed-methods cyclic evaluation process to assess and optimize the potential impact of the chlamydia page.

View Article and Find Full Text PDF

Evaluation of reporting trends in the MAUDE Database: 1991 to 2022.

Digit Health

January 2025

University of Haifa, School of Public Health, Head, Division of Health Systems Policy and Administration, Haifa, Israel.

Unlabelled: Adverse event reporting for medical devices is critical for risk mitigation. The Food and Drug Administration's (FDA) Manufacturer and User Facility Device Experience (MAUDE) database serves as a key tool for post-market surveillance, receiving reports from various sources. Ensuring information integrity, especially across diverse reporting sources, is paramount.

View Article and Find Full Text PDF

Background: Dementia is a widespread syndrome that currently affects more than 55 million people worldwide. Digital screening instruments are one way to increase diagnosis rates. Developing an app for older adults presents several challenges, both technical and social.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!