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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 explore the history of cognitive research in information systems (IS) across three major research streams in which cognitive processes are of paramount importance: developing software, decision support, and human-computer interaction. Through our historical analysis, we identify " enduring questions " in each area. The enduring questions motivated(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)
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)
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(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)
Human decision making is error-prone and often subject to biases. Important information cues are misweighted and feedback delays hamper learning. Experimentally, task information has been shown to be valuable in improving decision making. However, such information is rarely available. Generalizing from lab-based approaches, we present a new field(More)