Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases
Published Online:6 Mar 2015https://doi.org/10.1287/mnsc.2014.2026
References
- (2005) Competition and innovation: An inverted U relationship. Quart. J. Econom. 120(2):701–728.Google Scholar
- (2005) Privacy-Preserving Database Systems in Foundations of Security Analysis and Design III. Aldini A, Gorrieri R, Martinelli F, eds., Lecture Notes in Computer Science 3655 (Springer, Berlin), 178–206.Crossref, Google Scholar
- (2008) Database Marketing: Analyzing and Managing Customers (Springer, New York).Crossref, Google Scholar
- (2004) Nonparametric and semiparametric models for missing covariates in parametric regression. J. Amer. Statist. Assoc. 99(468):1176–1189.Crossref, Google Scholar
- (2007) A semiparametric odds ratio model for measuring association. Biometrics 63(2):413–421.Crossref, Google Scholar
- (1982) Data-swapping: A technique for disclosure control. J. Statist. Planning Inference 6(1):73–85.Crossref, Google Scholar
- (2013) Marketing science replication and disclosure policy. Marketing Sci. 32(1):1–3.Link, Google Scholar
- (2007) A primer on copulas for count data. ASTIN Bull. 37(2):475–515.Crossref, Google Scholar
- (2012) Privacy and Innovation, Lerner J, Stern S, eds. Innovation Policy and the Economy, Vol. 12 (National Bureau of Economic Research, Cambridge, MA), 65–89.Crossref, Google Scholar
- (2006) Design of robust business-to-business electronic marketplaces with guaranteed privacy. Management Sci. 52(11):1721–1736.Link, Google Scholar
- (2007) Comparison of semiparametric and parametric methods for estimating copulas. Comput. Statist. Data Anal. 51(6):2836–2850.Crossref, Google Scholar
- (2010) Perturbation of numerical confidential data via skew-t distributions. Management Sci. 56(2):318–333.Link, Google Scholar
- (2011) Protecting privacy against record linkage disclosure: A bounded swapping approach for numeric data. Inform. Systems Res. 22(4):774–789.Link, Google Scholar
- (1989) Generalized Linear Models, 2nd ed. (Chapman and Hall/CRC, Boca Raton, FL).Crossref, Google Scholar
- (2011) Data selection and procurement. Marketing Sci. 30(6):965–976.Link, Google Scholar
- (2007) Minimizing information loss and preserving privacy. Management Sci. 53(1):101–116.Link, Google Scholar
- (2011) Encryption and the loss of patient data. J. Policy Anal. Management 30(3):534–556.Crossref, Google Scholar
- (2013) Technopessimism is bunk. PBS (July 26), http://www.pbs.org/newshour/rundown/technopessimism-is-bunk/.Google Scholar
- (2003) A theoretical basis for perturbation methods. Statist. Comput. 13(4):329–335.Crossref, Google Scholar
- (2006) Data shuffling–A new masking approach for numerical data. Management Sci. 52(5):658–670.Link, Google Scholar
- (1995) Accessibility, security, and accuracy in statistical database: The case for the multiplicative fixed data perturbation approach. Management Sci. 41(9):1549–1564.Link, Google Scholar
- (1999) A general additive data perturbation method for database security. Management Sci. 45(10):1399–1415.Link, Google Scholar
- (2001) An improved security requirement for data perturbation with implications for E-commerce. Decision Sci. 32(4):683–698.Crossref, Google Scholar
- (1999) Large-scale quasi-Newton and partially separable optimization. Numerical Optimization, Springer Series in Operations Research and Financial Engineering (Springer-Verlag, New York), 222–249.Crossref, Google Scholar
- (2007) Do national patent laws stimulate domestic innovation in a global patenting environment? A cross-country analysis of pharmaceutical patent protection, 1978–2002. Rev. Econom. Statist. 89(3):436–453.Crossref, Google Scholar
- (2011) No customer left behind: A distribution-free Bayesian approach to account for missing xs in marketing models. Marketing Sci. 30(4):717–736.Link, Google Scholar
- (2014) Which brand purchasers are lost to counterfeits? An application of new data fusion approaches. Marketing Sci. 33(3):437–448.Link, Google Scholar
- (2009) Copula density estimation by total variation penalized likelihood. Comm. Statist. Simulation Comput. 38(9):1891–1908.Crossref, Google Scholar
- (2003) Multiple imputation for statistical disclosure limitation. J. Official Statist. 19(1):1–16.Google Scholar
- (2005) Releasing multiply-imputed, synthetic public use microdata: An illustration and empirical study. J. Royal Statist. Soc. Ser. A 168:185–205.Crossref, Google Scholar
- (2007) The multiple adaptations of multiple imputation. J. Amer. Statist. Assoc. 102(480):1462–1471.Crossref, Google Scholar
- (1993) Discussion: Statistical disclosure limitation. J. Official Statist. 9(2):461–468.Google Scholar
- (2002) Perturbing nonnormal confidential attributes: The copula approach. Management Sci. 48(12):1613–1627.Link, Google Scholar
- (1962) On the generation of normal random vectors. Technometrics 4(2):278–281.Crossref, Google Scholar
- (2001) Bureau blurs data to keep names confidential. Wall Street Journal (February 14):B1–B2.Google Scholar
- (2001) Elements of Statistical Disclosure Control (Springer, New York).Crossref, Google Scholar
- (2001) A framework for customer relationship management. California Management Rev. 43(4):89–105.Crossref, Google Scholar
- (2006) Personalized privacy preservation. Chaudhuri S, Hristidis V, Polyzotis N, eds. Proc. ACM SIGMOD Internat. Conf. Management of Data (Association for Computing Machinery, New York), 229–240.Crossref, Google Scholar

