Indicative Publications

@article{nokey,

title = {Speed matters: What to prioritize in optimization for faster websites},

author = {Ioannis C Drivas and Xilogianni Christina and Filippos Doukas and Dimitrios Kouis},

doi = {https://doi.org/10.3390/analytics1020012},

year  = {2022},

date = {2022-11-25},

urldate = {2022-11-25},

journal = {Analytics},

volume = {1},

issue = {2},

pages = {175-192},

abstract = {Website 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.},

keywords = {analytics, libraries, museums, performance, web analytics, website},

pubstate = {published},

tppubtype = {article}

}