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Why companies change privacy policies : A principal-agent perspective

Chipidza, Wallace; Leidner, Dorothy LU and Burleson, Debra (2016) 49th Annual Hawaii International Conference on System Sciences, HICSS 2016 In Proceedings of the Annual Hawaii International Conference on System Sciences 2016-March. p.4849-4858
Abstract

Companies often update their privacy policies, but it is unclear whether these updates strengthen or weaken user privacy. Using a principal-agent theoretical lens, we analyze over 200 changes to privacy policies of five prominent Internet companies over a period of fifteen years. We find that over time, privacy policy updates are more likely to weaken, rather than strengthen, user privacy on the Internet. Moreover, analysis of pilot data suggests that companies are more likely to update their privacy policies if they experience negative revenue growth over successive financial reporting periods. Since our results show that changes in privacy policies benefit companies at the expense of user privacy, we conclude that the principal-agent... (More)

Companies often update their privacy policies, but it is unclear whether these updates strengthen or weaken user privacy. Using a principal-agent theoretical lens, we analyze over 200 changes to privacy policies of five prominent Internet companies over a period of fifteen years. We find that over time, privacy policy updates are more likely to weaken, rather than strengthen, user privacy on the Internet. Moreover, analysis of pilot data suggests that companies are more likely to update their privacy policies if they experience negative revenue growth over successive financial reporting periods. Since our results show that changes in privacy policies benefit companies at the expense of user privacy, we conclude that the principal-agent problem exists in the information privacy arena.

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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Information asymmetry, Information privacy, Moral hazard, Principal-agent problem, Privacy policy
in
Proceedings of the Annual Hawaii International Conference on System Sciences
volume
2016-March
pages
10 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
49th Annual Hawaii International Conference on System Sciences, HICSS 2016
external identifiers
  • Scopus:84975471884
ISBN
9780769556703
DOI
10.1109/HICSS.2016.601
language
English
LU publication?
yes
id
922d8689-5ca8-46c2-a864-bcb799b55174
date added to LUP
2016-07-19 08:25:20
date last changed
2016-07-19 08:25:20
@misc{922d8689-5ca8-46c2-a864-bcb799b55174,
  abstract     = {<p>Companies often update their privacy policies, but it is unclear whether these updates strengthen or weaken user privacy. Using a principal-agent theoretical lens, we analyze over 200 changes to privacy policies of five prominent Internet companies over a period of fifteen years. We find that over time, privacy policy updates are more likely to weaken, rather than strengthen, user privacy on the Internet. Moreover, analysis of pilot data suggests that companies are more likely to update their privacy policies if they experience negative revenue growth over successive financial reporting periods. Since our results show that changes in privacy policies benefit companies at the expense of user privacy, we conclude that the principal-agent problem exists in the information privacy arena.</p>},
  author       = {Chipidza, Wallace and Leidner, Dorothy and Burleson, Debra},
  isbn         = {9780769556703},
  keyword      = {Information asymmetry,Information privacy,Moral hazard,Principal-agent problem,Privacy policy},
  language     = {eng},
  month        = {03},
  pages        = {4849--4858},
  publisher    = {ARRAY(0xb39fbc0)},
  series       = {Proceedings of the Annual Hawaii International Conference on System Sciences},
  title        = {Why companies change privacy policies : A principal-agent perspective},
  url          = {http://dx.doi.org/10.1109/HICSS.2016.601},
  volume       = {2016-March},
  year         = {2016},
}