IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i8p2432-d225558.html
   My bibliography  Save this article

An Empirical Study on User Experience Evaluation and Identification of Critical UX Issues

Author

Listed:
  • Lin Feng

    (Department of Economics, School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710049, China)

  • Wei Wei

    (Department of Economics, School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

We introduce an approach that supports researchers and practitioners to determine the quality of first-time user experience (FTUX) and long-term user experience (LTUX), as well as to identify critical issues with these two types of UX. The product we chose to study is a mobile fitness application. Mobile apps tend to have a much shorter service life than most other products; thus, the developers/designers need to pay great attention to both first-time and long-term user experience. This study is based on a multi-method approach. We employed the AttrakDiff questionnaire to assess users’ first impressions of the app, and the UX Curve method to evaluate how users’ experience of the app has changed over time. Besides the quantitative data, which helped to determine the quality of user experience, we also collected qualitative data during two interviews with participants, and focused on the issues that predominantly deteriorated user experience. A four-coordinate plane tool was designed later in the data analysis process that combined the two kinds of user experience data at the same time, which led to a qualitative positioning of the user experience status of a certain product. The model was further successfully adopted in the identification of user experience issues of an online fitness application.

Suggested Citation

  • Lin Feng & Wei Wei, 2019. "An Empirical Study on User Experience Evaluation and Identification of Critical UX Issues," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2432-:d:225558
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/8/2432/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/8/2432/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lin Feng & Baoping Sun & Kai Wang & Sang-Bing Tsai, 2018. "An Empirical Study on the Design of Digital Content Products from a Big Data Perspective," Sustainability, MDPI, vol. 10(9), pages 1-21, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin Feng & Wei Wei, 2020. "A Combined Method of r-NPS and t-NPS Evaluations for Identification of Negative Triggers of Detractors’ Experience," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
    2. Chi-Hung Lo & Yi-Wen Wang, 2019. "Constructing an Evaluation Model for User Experience in an Unmanned Store," Sustainability, MDPI, vol. 11(18), pages 1-29, September.
    3. Mashael Alghareeb & Abdulmohsen Saud Albesher & Amna Asif, 2023. "Studying Users’ Perceptions of COVID-19 Mobile Applications in Saudi Arabia," Sustainability, MDPI, vol. 15(2), pages 1-17, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chi-Hung Lo & Yi-Wen Wang, 2019. "Constructing an Evaluation Model for User Experience in an Unmanned Store," Sustainability, MDPI, vol. 11(18), pages 1-29, September.
    2. Sergio Pardo-Jaramillo & Andrés Muñoz-Villamizar & Ignacio Osuna & Rolando Roncancio, 2020. "Mapping Research on Customer Centricity and Sustainable Organizations," Sustainability, MDPI, vol. 12(19), pages 1-18, September.
    3. Shobhana Chandra & Sanjeev Verma, 2023. "Big Data and Sustainable Consumption: A Review and Research Agenda," Vision, , vol. 27(1), pages 11-23, February.
    4. Russell Tatenda Munodawafa & Satirenjit Kaur Johl, 2019. "Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies," Sustainability, MDPI, vol. 11(15), pages 1-21, August.
    5. Lin Feng & Wei Wei, 2020. "A Combined Method of r-NPS and t-NPS Evaluations for Identification of Negative Triggers of Detractors’ Experience," Sustainability, MDPI, vol. 12(4), pages 1-23, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2432-:d:225558. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.