Please use this identifier to cite or link to this item: https://rfos.fon.bg.ac.rs/handle/123456789/2913
Title: Uncovering the Hidden Insights of the Government AI Readiness Index: Application of Fuzzy LMAW and Schweizer-Sklar Weighted Framework
Authors: Nasution, Mahyuddin K. M.
Elveny, Marischa
Pamučar, Dragan 
Popović, Milena 
Gušavac Andrić, Bisera
Keywords: Artificial intelligence (AI);Oxford Insights AI Readiness Index;Weighting criteria;Non-linear analysis;Clustering analysis;AI readiness rankings
Issue Date: 9-Aug-2024
Abstract: There is considerable promising in artificial intelligence (AI) and algorithms, with governments worldwide increasingly investing in this transformative technology. The potential benefits include improved performance, cost reduction, efficient management, and crimeprediction and prevention, among others. The AI era holds the promise of revolutionizing various aspects of society. However, as countries prepare to leverage the power of artificial intelligence, questions arise about the validity of rankings published on the readiness of the governments for the application of AI. In this article, the weighting criteria that are analysed in the Oxford Insights AI Readiness Index are scrutinized, aiming to provide a more accurate assessment. Instead of conventional averaging, arithmetic and geometric non-linear functions are employed to analyse and assess the rank of the countries. Through clustering analysis, countries are categorized into three distinct groups based on observed criteria, offering a nuanced perspective on government AI readiness. This clustering approach not only facilitates a more effective categorization of countries based on their AI preparedness, but also accentuates the variations and similarities within each cluster, which enables deeper insights intoregional trends and pinpoint targeted strategies for enhancement within each cluster.
URI: https://rfos.fon.bg.ac.rs/handle/123456789/2913
ISSN: 2560-6018
Appears in Collections:Radovi istraživača / Researchers’ publications

Show full item record

SCOPUSTM   
Citations

6
checked on Nov 17, 2025

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons