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Abstract
In the post Snowden revelations era, concerns related to government surveillance and oversight have come to the forefront. The ability of the Internet to remember “everything” (or forget anything) also raises a privacy concern associated with the “right to be forgotten”. Hence, in this paper, we propose and examine privacy concerns by extending the Hong and Thong’s (2013) model with the addition of two dimensions: right to be forgotten as well as government surveillance and oversight. We tested two different measurement models using privacy concerns as a second-order and a third-order construct within a nomological net that includes trusting beliefs and willingness-to-share information for monetary gains, personalization, and national security. Data were collected from MTurk and analyzed using structural equation modeling. Findings provide support for the addition of the proposed dimensions.
Recommended Citation
Bansal, Gaurav and Nah, Fiona, "Measuring Privacy Concerns with Government Surveillance and Right-to-be-Forgotten in Nomological Net of Trust and Willingness-to-Share" (2020). AMCIS 2020 Proceedings. 31.
https://aisel.aisnet.org/amcis2020/info_security_privacy/info_security_privacy/31
Measuring Privacy Concerns with Government Surveillance and Right-to-be-Forgotten in Nomological Net of Trust and Willingness-to-Share
In the post Snowden revelations era, concerns related to government surveillance and oversight have come to the forefront. The ability of the Internet to remember “everything” (or forget anything) also raises a privacy concern associated with the “right to be forgotten”. Hence, in this paper, we propose and examine privacy concerns by extending the Hong and Thong’s (2013) model with the addition of two dimensions: right to be forgotten as well as government surveillance and oversight. We tested two different measurement models using privacy concerns as a second-order and a third-order construct within a nomological net that includes trusting beliefs and willingness-to-share information for monetary gains, personalization, and national security. Data were collected from MTurk and analyzed using structural equation modeling. Findings provide support for the addition of the proposed dimensions.
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