Management information systems: conceptual foundations, structure, and development (2nd ed.)
Management information systems: conceptual foundations, structure, and development (2nd ed.)
Data quality and due process in large interorganizational record systems
Communications of the ACM
Datamation
Implications of data quality for spreadsheet analysis
ACM SIGMIS Database
Assessing data reliability in an information system
Journal of Management Information Systems - Special Issue: Database Management
Optimal imputation of erroneous data: Categorical data, general edits
Operations Research
Integrity analysis: methods for automating data quality assurance
Information and Software Technology
Methodology for allocating resources for data quality enhancement
Communications of the ACM
Powers-of-ten information biases
MIS Quarterly
Information and Software Technology
Data quality: management and technology
Data quality: management and technology
Managing data quality in accounting information systems: a stochastic clearing system approach
Managing data quality in accounting information systems: a stochastic clearing system approach
Implications of errors in survey data: a Bayesian model
Management Science
The notion of data and its quality dimensions
Information Processing and Management: an International Journal
Estimating and improving the quality of information in a MIS
Communications of the ACM
The impact of data accuracy on system learning
Journal of Management Information Systems - Special section: Research in integrating learning capabilities into information systems
Journal of Management Information Systems - Special section: Realizing value from information technology investment
Four ethical issues of the information age
MIS Quarterly
How Do Actuaries Use Data Containing Errors?: Models of Error Detection and Error Correction
Information Resources Management Journal
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There is strong evidence that data stored in organizational databases have a significant rate of errors. As computerized databases continue to proliferate, the number of errors in stored data and the organizational impact of these errors are likely to increase. The impact of data errors on business processes and decision making can be lessened if users of information systems are able and willing to detect and correct data errors. However, some published research suggests that users of information systems do not detect data errors. This paper reports the results of a study showing that municipal bond analysts detect data errors. The results provide insight into the conditions under which users in organizational settings detect data errors. Guidelines for improving error detection are also discussed