• DSpace Universidad Indoamerica
  • Publicaciones Científicas
  • Artículos Científicos Indexados
  • Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/3018
    Title: Accessibility challenges of e-commerce websites
    Authors: Acosta-Vargas, Patricia
    Salvador-Acosta, Belén
    Salvador-Ullauri, Luis
    Jadán-Guerrero, Janio
    Issue Date: 2022
    Publisher: PeerJ Computer Science. Volume 8
    Abstract: Today, there are many e-commerce websites, but not all of them are accessible. Accessibility is a crucial element that can make a difference and determine the success or failure of a digital business. The study was applied to 50 e-commerce sites in the top rankings according to the classification proposed by ecommerceDB. In evaluating the web accessibility of e-commerce sites, we applied an automatic review method based on a modification of Website Accessibility Conformance Evaluation Methodology (WCAG-EM) 1.0. To evaluate accessibility, we used Web Accessibility Evaluation Tool (WAVE) with the extension for Google Chrome, which helps verify password-protected, locally stored, or highly dynamic pages. The study found that the correlation between the ranking of e-commerce websites and accessibility barriers is 0.329, indicating that the correlation is low positive according to Spearman’s Rho. According to the WAVE analysis, the research results reveal that the top 10 most accessible websites are Sainsbury’s Supermarkets, Walmart, Target Corporation, Macy’s, IKEA, H&M Hennes, Chewy, Kroger, QVC, and Nike. The most significant number of accessibility barriers relate to contrast errors that must be corrected for e-commerce websites to reach an acceptable level of accessibility. The most neglected accessibility principle is perceivable, representing 83.1%, followed by operable with 13.7%, in third place is robust with 1.7% and finally understandable with 1.5%. Future work suggests constructing a software tool that includes artificial intelligence algorithms that help the software identify accessibility barriers.
    URI: https://peerj.com/articles/cs-891/
    Appears in Collections:Artículos Científicos Indexados

    Files in This Item:
    There are no files associated with this item.

    This item is licensed under a Creative Commons License Creative Commons