The impact of user- and system-initiated personalization on the user experience at large sports events

Abstract

This article describes an experimental study investigating the impact on user experience of two approaches of personalization of content provided on a mobile device, for spectators at large sports events. A lab-based experiment showed that a system-driven approach to personalization was generally preferable, but that there were advantages to retaining some user control over the process. Usability implications for a hybrid approach, and design implications are discussed, with general support for countermeasures designed to overcome recognised limitations of adaptive systems.

App icon similarity and its impact on visual search efficiency on mobile touch devices

“…Overall, allowing more variability to icon design could both enhance efficiency and further empower users by offering user- and/or system-initiated personalization, as has been shown for other contexts (e.g. Sun, May, & Wang, 2016 ). Furthermore, it offers great possibilities to meet users’ needs for organization (Böhmer & Krüger, 2013 ) and for aesthetically pleasing icon design (e.g.…”

Ergonomics issues in sport and outdoor recreation

“…Cognitive ergonomics research has focused on various cognitive issues associated with individuals and teams, ranging from decision-making (Macquet and Fleurance 2007) and cognition (McNeese et al 2015) to situation awareness (Macquet and Stanton 2014;Neville and Salmon 2016), teamwork (Salmon, Clacy, and Dallat 2017a) and coaching (Macquet, Ferrand, and Stanton 2015). More recently, systems ergonomics applications have begun to explore wider sports systems issues such as performance analysis (Mclean et al, forthcoming), injury causation and prevention (Clacy et al, forthcoming) and spectators and crowds (Filingeri et al 2017;Sun, May, and Wang 2016).…”

User-Centered Design Approaches to Integrating Intellectual Property Information into Early Design Processes with a Design Patent Retrieval Application

“…All interview records were transcribed into text in Nvivo 11. An Emergent Themes Analysis (e.g., Braun & Clarke, 2006;Sun, May, & Wang, 2016) was conducted to understand the data. In the data analysis, the first step was to find a structure, a means of setting up the different interviews for the analysis; the second step was to remove any non-essential data from the texts; the third step was to code and categorise the data according to themes.…”