DC FieldValueLanguage
dc.contributor.authorKouis, Dimitrios-
dc.contributor.authorDrivas, Ioannis-
dc.contributor.authorXilogianni, Christina-
dc.contributor.authorDoukas, Filippos-Rafail-
dc.date.accessioned2023-10-10T12:22:46Z-
dc.date.available2023-10-10T12:22:46Z-
dc.date.issued2022-11-25-
dc.identifier.other123521996-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/51-
dc.description.abstractWebsite loading speed time matters when it comes to users’ engagement and conversion rate optimization. The websites of libraries, archives, and museums (LAMs) are not an exception to this assumption. In this research paper, we propose a methodological assessment schema to evaluate the LAMs webpages’ speed performance for a greater usability and navigability. The proposed methodology is composed of three different stages. First, the retrieval of the LAMs webpages’ speed data is taking place. A sample of 121 cases of LAMs worldwide has been collected using the PageSpeed Insights tool of Google for their mobile and desktop performance. In the second stage, a statistical reliability and validity analysis takes place to propose a speed performance measurement system whose metrics express an internal cohesion and consistency. One step further, in the third stage, several predictive regression models are developed to discover which of the involved metrics impact mostly the total speed score of mobile or desktop versions of the examined webpages. The proposed methodology and the study’s results could be helpful for LAMs administrators to set a data-driven framework of prioritization regarding the rectifications that need to be implemented for the optimized loading speed time of the webpages.en_US
dc.language.isoenen_US
dc.relation.ispartofAnalyticsen_US
dc.subjectWebsiteen_US
dc.subjectWebpageen_US
dc.subjectLoading timeen_US
dc.subjectSpeeden_US
dc.subjectOptimizationen_US
dc.subjectPageSpeed insightsen_US
dc.subjectLibrariesen_US
dc.subjectArchivesen_US
dc.subjectMuseumsen_US
dc.subjectLAMen_US
dc.titleSpeed Matters: What to Prioritize in Optimization for Faster Websitesen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/analytics1020012en_US
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume1en_US
dc.relation.issue2en_US
dc.identifier.spage175en_US
dc.identifier.epage192en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.countryGreeceen_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-5948-9766-
crisitem.author.orcid0000-0003-2407-9502-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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