State of the Art and Technology Innovation

Massaro, Alessandro

doi:10.1002/9781119716907.ch1

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…On the technological point of view the internet infrastructure is classified in different operation scale such as Local Area Network (LAN), Metropolitan Area Network (MAN), Wide Area Network (WAN) (A. Massaro, 2022). Different typologies characterize the network infrastructure such point-to-point connection, bus line, ring layout, star connection, tree layout; and node meshing (Massaro, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Massaro, 2022). Different typologies characterize the network infrastructure such point-to-point connection, bus line, ring layout, star connection, tree layout; and node meshing (Massaro, 2022). Landline technology tends to be developed in the sense of totally optical devices such as WDM wavelength Division Multiplexer (Massaro, et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Fixed Broadband Take-Up in Europe

Leogrande¹,

Magaletti²,

Cosoli³

et al. 2022

SSRN Journal

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fixed Broadband Take-Up in Europe

Leogrande¹,

Magaletti²,

Cosoli³

et al. 2022

SSRN Journal

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“…Technologically it is possible to classify the internet infrastructure in Local Area Network, Metropolitan Area Network and Wide Area Network [24]. The network infrastructure can be characterized by different typologies such as: star connection, tree layout, node meshing, point-to-point connection [25]. Fully optical devices such as WDM Wavelength Division Multiplexer can develop fixed line technology [26].…”

Section: Introductionmentioning

confidence: 99%

The Role of Broadband Price Index in Fostering Economic Growth and Digitization in Europe

Leogrande¹,

Magaletti²,

Cosoli³

et al. 2022

J. Hum. Earth Future

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This study analyzes the determinants of the "Broadband Price Index" in Europe. The data used refers to 28 European countries between 2016 and 2021. The database used is the Digital, Economy, and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index and "Connectivity", while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills", "Above Basic Digital Skills", and "At Least Basic Software Skills". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN, with an estimated value equal to an amount of 9.21%. Doi: 10.28991/HEF-2022-03-01-03 Full Text: PDF

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Fixed Broadband Take-Up in Europe

Leogrande¹,

Magaletti²,

Cosoli³

et al. 2022

Preprint

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In this article the value of “Fixed Broadband Take Up” in Europe is investigated. Data are collected from the DESI-Digital Economy and Society Index for 28 countries in the period 2016-2021. Data are analyzed with Panel Data with Fixed Effects and Random Effects. The Fixed Broadband Take-Up value is positively associated with the value of "Connectivity", "Human Capital", "Desi Index", "Fast BB NGA Coverage", "Fixed Very High-Capacity Network VHCN coverage". Fixed Broadband Take-Up value is negatively associated with "Digital Public Services for Businesses", "e-Government", "At least Basic Digital Skills", "At Least Basic Software Skills", "Above Basic Digital Skills", "Advanced Skills and Development", "Integration of Digital Technology", "Broadband Price Index", "Mobile Broadband", "Fixed Broadband Coverage". Subsequently the k-Means algorithm optimized by the Silhouette coefficient was used to identify the number of clusters. The analysis shows the presence of the two clusters. Eight different machine learning algorithms were then used to predict the future value of the "Fixed Broadband Take-Up in Europe". The analysis shows that the most efficient algorithm for the prediction is "ANN-Artificial Neural Network" with an estimated value of the prediction equal to 26.39%.

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State of the Art and Technology Innovation

Cited by 4 publications

References 43 publications

Fixed Broadband Take-Up in Europe

Fixed Broadband Take-Up in Europe

The Role of Broadband Price Index in Fostering Economic Growth and Digitization in Europe

Fixed Broadband Take-Up in Europe

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