The impact of poor data quality on the typical enterprise
Communications of the ACM
Communications of the ACM - Supporting community and building social capital
A Framework for Analysis of Data Quality Research
IEEE Transactions on Knowledge and Data Engineering
Beyond accuracy: what data quality means to data consumers
Journal of Management Information Systems
Time-Related Factors of Data Quality in Multichannel Information Systems
Journal of Management Information Systems
Journal of Management Information Systems
Measuring e-Commerce Success: Applying the DeLone & McLean Information Systems Success Model
International Journal of Electronic Commerce
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
Journal of Management Information Systems
Overview and Framework for Data and Information Quality Research
Journal of Data and Information Quality (JDIQ)
Methodologies for data quality assessment and improvement
ACM Computing Surveys (CSUR)
Information technology and productivity: Empirical evidence from the Chinese electronics industry
Information and Management
A Lag Effect of IT Investment on Firm Performance
Information Resources Management Journal
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Despite popular belief that timely and precise data are important and indispensable to good decisions and that good decisions are related to better firm performance, empirical research that examines the effect of data quality on firm performance is still scarce. How great an impact does data quality have on firm performance? This study empirically investigates the effect of firm-level data quality on firm performance in the Korean financial industry during 2008---2010. The results show that commercial banks have high-quality data, while credit unions have comparatively low-quality data. They also show that better data quality has a positive influence on sales, operating profit, and value added. Improving the level of data quality management maturity by one can increase firm performance by 33.7 % in sales, 64.4 % in operating profit, and 26.2 % in value added.