Michael J. Davern

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Prior efforts in personalization have focused primarily on modeling individual consumer’s preferences so that products for which they have a higher likelihood of purchasing are presented. In this study we explore the potential of an approach to personalization focusing on customizing shopping tools based on a consumer’s Product Category Knowledge. The low(More)
Information Systems (IS), as social artifacts, are open to interpretation during use. This flexibility creates opportunities for individuals to use systems in unanticipated ways to better fit particular tasks. Yet such unanticipated usage is counter to the use of IS as vehicles for managerial control and ensuring consistency in transaction processing across(More)
We discover and document errors in public-use microdata samples ("PUMS files") of the 2000 Census, the 2003-2006 American Community Survey, and the 2004-2009 Current Population Survey. For women and men age 65 and older, age- and sex-specific population estimates generated from the PUMS files differ by as much as 15 percent from counts in published data(More)
In the “quest” (Delone and McLean 1992) for reliable and practical measures of IS success, a growing stream of research has argued that a key predictor of performance impacts is user evaluations of fit between task requirements and characteristics of the system or technology (Goodhue and Thompson 1995; Vessey and Galletta 1991; Jarvenpaa 1989; Goodhue(More)
Online merchants use personalization technologies to gain knowledge of an individual customer and then generate preference-matched web content for the customer. Among the various types of personalization technologies, this research focuses on personalization engines that generate preference-matched content based on a customer's prior transactions. Extant(More)
From the prospective traveler surfing the web for cheap vacations to executives analyzing market trends with a data warehouse, at home and at work, people are confronted with increasingly richer information environments. This study is an attempt at modeling the behavior over-time of the “information consumer” (web surfer or executive) in such environments.(More)
Virtually all quantitative microdata used by social scientists derive from samples that incorporate clustering, stratification, and weighting adjustments (Kish 1965, 1992). Such data can yield standard error estimates that differ dramatically from those derived from a simple random sample of the same size. Researchers using historical U.S. census microdata,(More)
A breakthrough in the tradeoff between privacy and data quality has been achieved for restricted access to population census microdata samples. The IPUMS-International website, as of June 2006, offers integrated microdata for 47 censuses, totaling more than 140 million person records, with 13 countries represented. Over the next four years, the global(More)