NDLI: Analysis of Cross-Border Data Trade Restrictions Using Mixture-Based Clustering

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Analysis of Cross-Border Data Trade Restrictions Using Mixture-Based Clustering

Content Provider	Scilit
Author	Huang, Keman Chinnery, Samuel Madnick, Stuart E.
Copyright Year	2019
Description	Journal: SSRN Electronic Journal Cross-border data flows and interoperability have created an increasingly digital global trade environment. Concerns for cybersecurity, privacy, and digital sovereignty have prompted the widespread implementation of trade policies regulating cross-border data flows. At present, there is a deficit of information characterizing such policies and analyzing their role in the global economy. We address this deficit through a quantitative analysis of trade policies in services that seeks both to categorize data-related trade policies and to evaluate the extent to which they are different from other restrictive measures. We propose a mixture-based clustering pipeline to group trade restrictiveness data and a method for quantifying the difference between the cross-border data flow regulations and other traditional regulations. Our analysis reveals a significant localization effect among data flow restrictions and that, while highly restrictive data flow policies generally do not overlap with other policies, there is a significant similarity in moderate to liberal policies.
Related Links	https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1319&context=amcis2019 https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=3455603
ISSN	10914358
e-ISSN	15565068
DOI	10.2139/ssrn.3455603
Journal	SSRN Electronic Journal
Language	English
Publisher	Elsevier BV
Publisher Date	2019-03-01
Access Restriction	Open
Subject Keyword	Journal: SSRN Electronic Journal Information and Library Science Trade Restrictiveness Data Border Data Flows Cross Border Data Flow
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health Psychiatry and Mental Health

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