scholarly journals The Economic Consequences of Data Privacy Regulation: Empirical Evidence from GDPR

2020 ◽  
Author(s):  
Guy Aridor ◽  
Yeon-Koo Che ◽  
William Nelson ◽  
Tobias Salz
Keyword(s):  
Empirical Evidence ◽  
Data Privacy ◽  
Economic Consequences ◽  
Privacy Regulation

scholarly journals Bought and Sold: Exploring the Effects of Big Data on User Agency and Commodification

2021 ◽  
Author(s):  
Kristia M. Pavlakos
Keyword(s):  
Social Sciences ◽  
Big Data ◽  
Data Privacy ◽  
Large Data ◽  
Data Sets ◽  
Privacy Regulation ◽  
Scholarly Literature ◽  
User Interests ◽  
The Social ◽  
The Relationship

Big Data1is a phenomenon that has been increasingly studied in the academy in recent years, especially in technological and scientific contexts. However, it is still a relatively new field of academic study; because it has been previously considered in mainly technological contexts, more attention needs to be drawn to the contributions made in Big Data scholarship in the social sciences by scholars like Omar Tene and Jules Polonetsky, Bart Custers, Kate Crawford, Nick Couldry, and Jose van Dijk. The purpose of this Major Research Paper is to gain insight into the issues surrounding privacy and user rights, roles, and commodification in relation to Big Data in a social sciences context. The term “Big Data” describes the collection, aggregation, and analysis of large data sets. While corporations are usually responsible for the analysis and dissemination of the data, most of this data is user generated, and there must be considerations regarding the user’s rights and roles. In this paper, I raise three main issues that shape the discussion: how users can be more active agents in data ownership, how consent measures can be made to actively reflect user interests instead of focusing on benefitting corporations, and how user agency can be preserved. Through an analysis of social sciences scholarly literature on Big Data, privacy, and user commodification, I wish to determine how these concepts are being discussed, where there have been advancements in privacy regulation and the prevention of user commodification, and where there is a need to improve these measures. In doing this, I hope to discover a way to better facilitate the relationship between data collectors and analysts, and user-generators. 1 While there is no definitive resolution as to whether or not to capitalize the term “Big Data”, in capitalizing it I chose to conform with such authors as boyd and Crawford (2012), Couldry and Turow (2014), and Dalton and Thatcher (2015), who do so in the scholarly literature.

scholarly journals Where has the rum gone? The impact of maritime piracy on trade and transport

2021 ◽  
Author(s):  
Alexander Sandkamp ◽  
Vincent Stamer ◽  
Shuyao Yang
Keyword(s):  
Empirical Evidence ◽  
Economic Consequences ◽  
Firm Level ◽  
Maritime Piracy ◽  
Exporting Firms ◽  
Maritime Shipping ◽  
Position Data ◽  
The Impact

AbstractDespite a general agreement that piracy poses a significant threat to maritime shipping, empirical evidence regarding its economic consequences remains scarce. This paper combines firm-level Chinese customs data and ship position data with information on pirate attacks to investigate how exporting firms and cargo ships respond to maritime piracy. It finds that overall exports along affected shipping routes fall following an increase in pirate activity. In addition, piracy induces firms to switch from ocean to air shipping, while remaining ocean shipments become larger. At the ship-level, the paper provides evidence for re-routing, as container ships avoid regions prone to pirate attacks.

scholarly journals Bought and Sold: Exploring the Effects of Big Data on User Agency and Commodification

2021 ◽  
Author(s):  
Kristia M. Pavlakos
Keyword(s):  
Social Sciences ◽  
Big Data ◽  
Data Privacy ◽  
Large Data ◽  
Data Sets ◽  
Privacy Regulation ◽  
Scholarly Literature ◽  
User Interests ◽  
The Social ◽  
The Relationship

Big Data1is a phenomenon that has been increasingly studied in the academy in recent years, especially in technological and scientific contexts. However, it is still a relatively new field of academic study; because it has been previously considered in mainly technological contexts, more attention needs to be drawn to the contributions made in Big Data scholarship in the social sciences by scholars like Omar Tene and Jules Polonetsky, Bart Custers, Kate Crawford, Nick Couldry, and Jose van Dijk. The purpose of this Major Research Paper is to gain insight into the issues surrounding privacy and user rights, roles, and commodification in relation to Big Data in a social sciences context. The term “Big Data” describes the collection, aggregation, and analysis of large data sets. While corporations are usually responsible for the analysis and dissemination of the data, most of this data is user generated, and there must be considerations regarding the user’s rights and roles. In this paper, I raise three main issues that shape the discussion: how users can be more active agents in data ownership, how consent measures can be made to actively reflect user interests instead of focusing on benefitting corporations, and how user agency can be preserved. Through an analysis of social sciences scholarly literature on Big Data, privacy, and user commodification, I wish to determine how these concepts are being discussed, where there have been advancements in privacy regulation and the prevention of user commodification, and where there is a need to improve these measures. In doing this, I hope to discover a way to better facilitate the relationship between data collectors and analysts, and user-generators. 1 While there is no definitive resolution as to whether or not to capitalize the term “Big Data”, in capitalizing it I chose to conform with such authors as boyd and Crawford (2012), Couldry and Turow (2014), and Dalton and Thatcher (2015), who do so in the scholarly literature.

Sequencing, Layering, and Feedbacks in Global Regulation

2016 ◽  
Author(s):  
Abraham L. Newman
Keyword(s):  
International Organizations ◽  
Data Privacy ◽  
Historical Institutionalism ◽  
Global Politics ◽  
International Affairs ◽  
Informal Networks ◽  
Global Regulation ◽  
Privacy Regulation ◽  
Domestic Law ◽  
Cross National

From banking standards to data privacy, regulation has entered the lexicon of international affairs. Unlike trade or currencies, however, there are few formal treaty-based international organizations resolving disputes or setting the rules for the world. Instead, global regulation is frequently shaped by informal networks of regulators or at times by the extraterritorial extension of domestic law by large markets. Drawing on work from historical institutionalism, this chapter argues that the global politics of regulation is in important respects the product of domestic and international institutions interacting over time and across space. In developing three mechanisms—relative sequencing, cross-national layering, and transnational feedbacks —the chapter argues that historical institutionalism helps address lacunae in extant approaches to global regulation.

Designing privacy-friendly data repositories: a framework for a blockchain that follows the GDPR

2020 ◽  
Vol 22 (5/6) ◽  
pp. 389-411
Author(s):  
Muhammad Al-Abdullah ◽  
Izzat Alsmadi ◽  
Ruwaida AlAbdullah ◽  
Bernie Farkas
Keyword(s):  
Computer Science ◽  
Data Privacy ◽  
Security And Privacy ◽  
Data Repository ◽  
Privacy Risk ◽  
Data Repositories ◽  
Privacy Regulation ◽  
Content Type ◽  
Blockchain Technology ◽  
Architectural Tactics

Purpose The paper posits that a solution for businesses to use privacy-friendly data repositories for its customers’ data is to change from the traditional centralized repository to a trusted, decentralized data repository. Blockchain is a technology that provides such a data repository. However, the European Union’s General Data Protection Regulation (GDPR) assumed a centralized data repository, and it is commonly argued that blockchain technology is not usable. This paper aims to posit a framework for adopting a blockchain that follows the GDPR. Design/methodology/approach The paper uses the Levy and Ellis’ narrative review of literature methodology, which is based on constructivist theory posited by Lincoln and Guba. Using five information systems and computer science databases, the researchers searched for studies using the keywords GDPR and blockchain, using a forward and backward search technique. The search identified a corpus of 416 candidate studies, from which the researchers applied pre-established criteria to select 39 studies. The researchers mined this corpus for concepts, which they clustered into themes. Using the accepted computer science practice of privacy by design, the researchers combined the clustered themes into the paper’s posited framework. Findings The paper posits a framework that provides architectural tactics for designing a blockchain that follows GDPR to enhance privacy. The framework explicitly addresses the challenges of GDPR compliance using the unimagined decentralized storage of personal data. The framework addresses the blockchain–GDPR tension by establishing trust between a business and its customers vis-à-vis storing customers’ data. The trust is established through blockchain’s capability of providing the customer with private keys and control over their data, e.g. processing and access. Research limitations/implications The paper provides a framework that demonstrates that blockchain technology can be designed for use in GDPR compliant solutions. In using the framework, a blockchain-based solution provides the ability to audit and monitor privacy measures, demonstrates a legal justification for processing activities, incorporates a data privacy policy, provides a map for data processing and ensures security and privacy awareness among all actors. The research is limited to a focus on blockchain–GDPR compliance; however, future research is needed to investigate the use of the framework in specific domains. Practical implications The paper posits a framework that identifies the strategies and tactics necessary for GDPR compliance. Practitioners need to compliment the framework with rigorous privacy risk management, i.e. conducting a privacy risk analysis, identifying strategies and tactics to address such risks and preparing a privacy impact assessment that enhances accountability and transparency of a blockchain. Originality/value With the increasingly strategic use of data by businesses and the contravening growth of data privacy regulation, alternative technologies could provide businesses with a means to nurture trust with its customers regarding collected data. However, it is commonly assumed that the decentralized approach of blockchain technology cannot be applied to this business need. This paper posits a framework that enables a blockchain to be designed that follows the GDPR; thereby, providing an alternative for businesses to collect customers’ data while ensuring the customers’ trust.

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