Paper Info
Title
An artificial intelligence method for digital government assessment: An application of neural networks analysis of a ranking of digital government of Mexican states.
Abstract
Development of accurate measurement systems to assess digital government advance is a critical topic of digital agenda of academia and governments around the world. There are several quantitative approaches such as rankings and indicators that have contributed to measure the progress of digital government initiatives in the public sector, but more sophisticated computational tools are usually unexploited. This article proposes a computational multi-parametric analysis of multiple metrics of digital government advance using a computational technique, the neural networks, for the analysis of the evolution of digital government ranking of Mexican states during the period 2009-2015. Neural networks analysis has been used in different areas such as scientometric performance profiles, and disciplines like physics, chemistry, management, economics and demography. The neural networks analysis helps to identify clusters of characterizations that represents digital government advance patterns of performance. It also locates various profiles of digital government progress with similar patterns of performance and atypical behaviors (outliers) which are difficult to identify with classical tools. The results of this computational technique are robust showing that artificial intelligence tools are useful instruments to evaluate digital government advance overtime.
Year
DOI
Venue
2017
10.1145/3085228.3085311
DG.O
Keywords
Field
DocType
Digital government, Assessment, Measurement, Neural networks
Data science,Computational Technique,Ranking,Computer science,Digital government,Outlier,Artificial intelligence,Public sector,Artificial neural network,Management science
Conference
Citations 
PageRank 
References 
0
0.34
12
Authors
2
Name
Order
Citations
PageRank
E. A. Villaseñor-García100.34
Gabriel Puron-Cid2398.91