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Investment in Privacy-Preserving Technologies under Uncertainty

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7037))

Abstract

Entrepreneurs face investment decisions on privacy-preserving technology (PPT) adoption as privacy-concerned consumers may decide whether to use firms’ services based on the extent of privacy that firms are able to provide. Kantarcioglu et.al. (2010) [9] contributes to guidelines for entrepreneurs’ adoption decisions through a novel framework, which combines copula functions and a Stackelberg leader-follower game with consumers taking the role of the follower (referred as static-copula-game model hereafter). The valuation requires a clearly defined bivariate distribution function of two random variables, the consumer’s valuation of private information and the consumer’s profitability to a firm. Copula functions are used to construct the bivariate distribution function from arbitrarily univariate marginals with various dependence structures fitting into different market/industry segments. This study extends the static-copula-game model to include project value uncertainty, simultaneously considering different market competition structures and the regulatory promise of random arrival of government mandatory adoption. The project value from the static-copula-game model is used as an estimate of the initial (current) project value for the stochastic evolution. By doing so, we retain the advantages of applying copulas and preserve the established valuation property exclusively applicable to the valuation of PPT adoption. The extension model makes several improvements including: (1) Reduce concerns about myopic PPT adoption decisions that may result when static valuation is employed. (2) Overcome the potential biased PPT adoption decision that may arise due to negligence of market competition impact. (3) Understand the regulatory influence of government mandatory adoption with uncertainty. We find that: (1) If one can link univariate marginals and dependence structures to industry groups, one can determine for which industries project value uncertainty has no impact on the entrepreneur’s immediate PPT adoption decision. For these industries, there is no need for government intervention/regulation to accelerate/induce PPT adoption even though the project value is uncertain. (2) Under project value uncertainty, competition may suggest either a later or an earlier PPT adoption compared with the monopoly case. (3) The promise of government mandatory adoption has the potential to accelerate PPT adoption. The PPT adoption guidelines considering competition and regulatory promises of government mandatory adoption when the project value is uncertain bring useful recommendations to both entrepreneurs and policymakers.

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References

  1. Acquisiti, A., Grossklags, J.: Losses, Gains, and Hyperbolic Discounting: An Experimental Approach to Information Security Attitudes and Behavior. In: Proc. 2nd Intl. Workshop Economics and Info. Security (2003)

    Google Scholar 

  2. Chellappa, R.K., Shivendu, S.: Managing Piracy: Pricing and Sampling Strategies for Digital Experience Goods in Vertically Segmented Markets. Information Systems Research 16(4), 400–417 (2005)

    Article  Google Scholar 

  3. Chellappa, R.K., Sin, R.: Personalization Versus Privacy: An Empirical Examination of the Online Consumers’ Dilemma. Information Technology and Management 6(2-3) (2005)

    Google Scholar 

  4. Dixit, A., Pindyck, R.S.: Investment Under Uncertainty. Princeton University Press (1994)

    Google Scholar 

  5. Huberman, B.A., Adar, E., Fine, L.R.: Valuating Privacy. IEEE Security & Privacy 3(5), 22–25 (2005)

    Article  Google Scholar 

  6. Olson, G., Olson, J.: Human-computer Interaction: Psychological Aspects of the Human Use of Computing. Annual Review of Psychology 54, 491 (2003)

    Article  Google Scholar 

  7. Hann, I.H., Hui, K.L., Lee, S.-Y.T., Png, I.P.L.: Overcoming Online Information Privacy Concerns: An Information-Processing Theory Approach. Journal of Management Information Systems 24(2), 13–42 (2007)

    Article  Google Scholar 

  8. Hunker, J.: A Privacy Expectations and Security Assurance Offer System. In: NSPW 2007, North Conway, NH, USA, September 18-21 (2007)

    Google Scholar 

  9. Kantarcioglu, M., Bensoussan, A., Hoe, S(C.): When Do Firms Invest in Privacy-Preserving Technologies? In: Alpcan, T., Buttyán, L., Baras, J. (eds.) GameSec 2010. LNCS, vol. 6442, pp. 72–86. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  10. Spiekermann, S., Grossklags, J., Berendt, B.: E-Privacy in Second Generation E-Commerce: Privacy Preferences versus Actual Behavior. In: Proc. ACM Conf. Electronic Commerce, pp. 38–47. ACM Press (2001)

    Google Scholar 

  11. Tang, Z., Hu, Y., Smith, M.D.: Protecting Online Privacy: Self-Regulation, Mandatory Standards, or Caveat Emptor. In: Proc. 4rth Annual Workshop on Economics and Information Security (2005)

    Google Scholar 

  12. Consumers and Health Information Technology: A National Survey. California Health Foundation (April 2010)

    Google Scholar 

  13. Diaspora: NYU Students Develop Privacy-Based Social Network, http://www.huffingtonpost.com/2010/05/11/diaspora-nyu-students-dev_n_571632.html

  14. FTC Regulation of Behavioral Advertising, http://en.wikipedia.org/wiki/FTC_Regulation_of_Behavioral_Advertising

  15. FTC: Privacy Self-Regulation Not Enough, Do Not Track Needed, http://gigaom.com/2010/12/01/ftcprivacydonottrack/

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© 2011 Springer-Verlag Berlin Heidelberg

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Kantarcioglu, M., Bensoussan, A., Hoe, S. (2011). Investment in Privacy-Preserving Technologies under Uncertainty. In: Baras, J.S., Katz, J., Altman, E. (eds) Decision and Game Theory for Security. GameSec 2011. Lecture Notes in Computer Science, vol 7037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25280-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-25280-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25279-2

  • Online ISBN: 978-3-642-25280-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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