A field experiment comparing information-privacy values, beliefs, and attitudes across several types of organizations.
Abstract
South Bend, IndianaThe present study examined (a) the effect of organizational type (a manipulatedvariable) on individuals' information-privacy values, beliefs, attitudes, and be-havioral intentions and (b) relationships between the same measured variablesSix organizational types were used (1 e., employers, insurance companies, lawenforcement agencies, credit grantors, lending institutions, and the Internal Rev-enue Service). Data on the dependent variables were obtained through the useof structured interviews involving 193 randomly selected residents of a mid-western state Multivanate and univanate analyses revealed (a) significant dif-ferences among the organizational types on information-privacy values, beliefs,and attitudes, and (b) significant correlations between these and other measuredvanables The implications of these findings for organizational and societal policymaking concerning the treatment of information about individuals are discussed
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Some blockchain research solutions and platforms such as Tangle or Wanchain employ crypto-algorithms resistant to quantum computing.
“some blockchain research solutions [92], and platforms such as Tangle [93] or Wanchain [19] employ crypto-algorithms resistant to quantum computing.”
From Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019) · cites this paper as [19]
In [19], storeman nodes keep part of the private keys of a source chain account, and manage a smart contract that locks the asset on the original chain, avoiding that a node can access the full private key of such original account.
“In this case, storeman nodes (groups of entities) keep part of the private keys of a source chain account, and manage a smart contract that locks the asset on the original chain, avoiding that a node can access to the full private key of such as original account.”
From Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019) · cites this paper as [19]
In blockchain, SMPC can be used for splitting the smart-contract execution as well as account and key management without requiring any third-party participation, as proposed in [19].
“In blockchain, SMPC can be used for splitting the smart-contract execution as well as account and key management without requiring any third-party participation, as proposed in [19], a ledger aimed to enable the exchange of digital assets among different blockchain networks.”
From Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019) · cites this paper as [19]
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- Authors
- Stone, E. F., Gueutal, H. G., Gardner, D. G., & McClure, S.
- Affiliations
- New York University (US)
- ORCID
- Gardner, Donald G.
- Venue
- Journal of Applied Psychology
- Published
- 1983-08
- Volume
- 68
- Issue
- 3
- Pages
- 459-468
- ISSN
- 0021-9010 (ISSN-L)
- 1939-1854
- OpenAlex
- W2039669983
- Cited by
- 387
- References
- 10
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 10 · 2023: 17 · 2022: 20 · 2021: 20 · 2020: 32 · 2019: 22 · 2018: 21 · 2017: 16 · 2016: 19 · 2015: 11 · 2014: 20 · 2013: 15 · 2012: 14
- FWCI
- 5.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Applied Psychology (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- data privacy, privacy attitudes, privacy values, behavioral intention, organizational type, insurance companies, law enforcement agencies, credit institutions, Internal Revenue Service, personal information disclosure, privacy policies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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