IS

McQuaid, Michael

Research Interests (6)

List of Topics (6)

Topic Weight Topic Terms
0.188 data database administration important dictionary organizations activities record increasingly method collection records considered perturbation requirements
0.151 approach analysis application approaches new used paper methodology simulation traditional techniques systems process based using
0.121 structural pls measurement modeling equation research formative squares partial using indicators constructs construct statistical models
0.113 data used develop multiple approaches collection based research classes aspect single literature profiles means crowd
0.105 privacy information concerns individuals personal disclosure protection concern consumers practices control data private calculus regulation
0.104 business digital strategy value transformation economy technologies paper creation digitization strategies environment focus net-enabled services

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List of Coauthors (1)

Melville, Nigel 1

Article Keywords (12)

Bayesian bootstrap 1 business value of information technology 1 confidentiality 1 data masking 1
data safety 1 data security 1 decision support systems 1 disclosure risk 1
Monte Carlo simulation 1 multimodal perturbation 1 multiple imputation 1 privacy 1

Articles (1)

Generating Shareable Statistical Databases for Business Value: Multiple Imputation with Multimodal Perturbation. (Information Systems Research, 2012)
Authors: Abstract:
    Business organizations are generating growing volumes of data about their employees, customers, and suppliers. Much of these data cannot be exploited for business value due to privacy and confidentiality concerns. National statistical agencies share sensitive data collected from individuals and businesses by modifying the data so individuals and firms cannot be identified but statistical utility is preserved. We build on this literature to develop a hybrid approach to data masking for business organizations. We demonstrate the validity of the hybrid approach, which we call multiple imputation with multimodal perturbation (MIMP), using Monte Carlo simulation and illustrate its application in a specific business context. Results of our analysis open new areas of research for information systems scholarship and new potential revenue sources for business organizations.