Policy making for broadband adoption and usage in Chile through machine learning

作者：

Highlights：

• We study the influential factors for adoption and usage of broadband Internet.

• Policies are proposed and evaluated using machine learning.

• Factors found: digital literacy, income, age, sex, # family members, education.

• Unconditional subsidy for the internet price is not appropriate for every household.

• Policies: incorporation of computers, internet applications, digital training.

摘要

•We study the influential factors for adoption and usage of broadband Internet.•Policies are proposed and evaluated using machine learning.•Factors found: digital literacy, income, age, sex, # family members, education.•Unconditional subsidy for the internet price is not appropriate for every household.•Policies: incorporation of computers, internet applications, digital training.

论文关键词：Broadband penetration,Policy making,Clustering analysis,Bayesian networks

论文评审过程：Available online 27 June 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.06.039