Return to search

User perspectives and usability insights in a self-service portal : Uncovering Opportunities for enhancing the user experience

In the era of digital transformation, the need for more efficient self-service technologies has increased, particularly after the COVID-19 pandemic, which highlighted the importance of reducing physical interactions. Although there is some research on self-service technologies, there is a lack of research on the usability of internal self-service portals which are used within organizations. This study aims to address this gap by applying the Technology Acceptance Model (TAM) and the design principles within Human-Computer Interaction (HCI) field to examine the usability of a self-service portal in a university in Sweden. The study adopts a mixed-method approach, incorporating data collection techniques such as cognitive walkthrough and semi-structured interviews for qualitative data, as well as System Usability Scale (SUS) questionnaire, and some other quantitative measurements for collecting data. Findings from the quantitative analysis through the System Usability Scale (SUS) results indicate a good to borderline OK design, with user satisfaction affected by the number of clicks and time required to complete tasks.  Findings from the qualitative analysis reveal important factors influencing user experience, including user perception of the portal's design, learnability, impact of access to multiple systems, influence of easy-to-reach IT assistance, impact of insufficient information and guidance, lack of awareness, user desires, and suggestions for the design. The study concludes with the development of design guidelines based on the identified themes, aiming to enhance the usability of the self-service portal. These findings contribute to the understanding of self-service portals' usability within organizational contexts and provide actionable recommendations for improving the design and the user experience.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-123369
Date January 2023
CreatorsMatloobtalab, Mehrnaz, Iversen, Philip
PublisherLinnéuniversitetet, Institutionen för informatik (IK)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

Page generated in 0.0019 seconds