Adequacy of data protection in the USA: myths and facts

Determann, Lothar

doi:10.1093/idpl/ipw011

Cited by 13 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both models were developed in the US, which allow certain data DOI 10.18502/kss.v8i1.12657 practices not allowed in Europe, e.g. automated processing of personal information [35]. Furthermore, with the General Data Protection Regulation, the European Union has shown that it takes data privacy and security very seriously.…”

Section: Discussionmentioning

confidence: 99%

Cash in the Trash? An Austrian Perspective on Mobile Payment Adoption

Bernardi

Ploder

Spieß

et al. 2023

KSS

View full text Add to dashboard Cite

Despite offering many benefits to consumers, merchants, banks, and other providers, mobile payment still has not found widespread acceptance in Austria, for example, in 2015, 15% of Austrian consumers used the Internet or a mobile device for payments and 16% made contactless payments at least once a week. This study sheds light on this issue by taking a consumer perspective and investigating the factors that foster or hinder mobile payment adoption. Three popular user acceptance models were compared and in the end, a unified theory of acceptance and use of technologybased model (UTAUT2) was chosen. The developed model was composed of 12 factors (behavioral intention, utilitarian performance expectancy, hedonic performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, perceived security, privacy concerns, trust, cost, personal innovativeness) and three moderators (age, gender, experience). The proposed model was tested using data from 158 Austrian consumers and analyzed with partial least squares structural equation modeling (PLS-SEM). The results showed that 68% of consumers’ intention to use mobile payments could be explained, making it a promising model in the mobile payment research area based on the baseline data. Perceived risk and hedonic performance expectancy are the greatest drivers with psychological risk (a lack of fit with one’s self-image) as the most important risk dimension. The results suggest that mobile payment possesses lifestyle characteristics and its usage needs to be fun in order for consumers to prefer it to cash and cards. Keywords: mobile payment adoption, unified theory of acceptance and use of technology, user acceptance models, partial least squares structural equation modeling

show abstract

Section: Discussionmentioning

confidence: 99%

Cash in the Trash? An Austrian Perspective on Mobile Payment Adoption

Bernardi

Ploder

Spieß

et al. 2023

KSS

View full text Add to dashboard Cite

show abstract

“…At the same time, a growing number of regions or countries have promulgated laws, policies, or regulations to respond to privacy and security issues in data. For example, the European Union issued the General Data Protection Regulation (Voigt & Von, 2017) and the Personal Information Protection Law by China (Determann et al, 2021). As a result, technical solutions for monitoring CEOs' facial fatigue while preserving personal information are urgently needed.…”

Section: Fatigue Monitoringmentioning

confidence: 99%

Smart work package learning for decentralized fatigue monitoring through facial images

Zeng

Chen

et al. 2022

Computer aided Civil Eng

View full text Add to dashboard Cite

Monitoring the fatigue of construction equipment operators (CEOs) is critical for preventing accidents and ensuring precision construction occupational health and safety (COHS). However, there exists a theoretical dilemma between centralized technical efficiency and decentralized data privacy. Thus, this study introduces smart work package learning (SWPL), a decentralized deep learning approach to monitor CEOs’ fatigue without privacy exposure risks. To illustrate the feasibility of SWPL as the fatigue classifier, this study implements fatigue monitoring through noninvasive facial images, and SWPL merges the updated parameters of the model from each smart work package (SWP). These updates are then validated by SWPs in the blockchain network and stored on the blockchain. More than 356 videos were derived from 124 operators. The results present that SWPL on decentralized SWP networks outperforms the deep learning model on individual SWP. The computational novelty is SWPL's dynamic parameter aggregation mechanism to avoid parameter exposure in centralized or fixed aggregators. The proposed SWPL will open up advanced developments in precision COHS.

show abstract

“…Article 29 Working Party, 2016). However, the European Commission has also decided that data can be transferred to states that are not particularly renowned for their data protection regimes, including Argentina, Israel, Uruguay and New Zealand (European Commission, 2016), having deemed that those states offer an adequate level of protection of data (Determann, 2016). As regards the Privacy Shield, it remains to be seen how the results of the 2016 Presidential election in the United States will impact upon the perceived sufficiency of data protection there.…”

Section: The Right To Data Protection and In An Era Of Big Datamentioning

confidence: 99%

Conceptualising the right to data protection in an era of Big Data

McDermott

2017

Big Data & Society

View full text Add to dashboard Cite

In 2009, with the enactment of the Lisbon Treaty, the Charter of Fundamental Rights of the European Union entered into force. Under Article 8 of the Charter, for the first time, a stand-alone fundamental right to data protection was declared. The creation of this right, standing as a distinct right to the right to privacy, is undoubtedly significant, and it is unique to the European legal order, being absent from other international human rights instruments. This commentary examines the parameters of this new right to data protection, asking what are the principles underpinning the right. It argues that the right reflects some key values inherent in the European legal order, namely: privacy, transparency, autonomy and nondiscrimination. It also analyses some of the challenges in implementing this right in an era of ubiquitous veillance practices and Big Data.

show abstract

Adequacy of data protection in the USA: myths and facts

Cited by 13 publications

References 0 publications

Cash in the Trash? An Austrian Perspective on Mobile Payment Adoption

Cash in the Trash? An Austrian Perspective on Mobile Payment Adoption

Smart work package learning for decentralized fatigue monitoring through facial images

Conceptualising the right to data protection in an era of Big Data

Contact Info

Product

Resources

About