Total data quality management: A study of bridging rigor and relevance

Proceedings of the 15th European Conference on Information Systems, ECIS 2007

Volumn , Issue , 2007, Pages 925-937

  Wijnhoven, Fons ^a   Boelens, Roy ^b   Middel, Rick ^a   Louissen, Kor ^c  

^a UNIVERSITY OF TWENTE   (Netherlands)

^b SG Automatisering   (Netherlands)

^c HONEYWELL   (United States)

Author keywords

Applicability of theory; Design science; Total data quality management

Indexed keywords

APPLICABILITY OF THEORY; DATA QUALITY; DATA QUALITY MANAGEMENT; DESIGN SCIENCE; HONEYWELL; TEAM COMPOSITION; TOOLSETS;

DESIGN; INFORMATION SYSTEMS; QUALITY MANAGEMENT;

DATA REDUCTION;

EID: 84869426423     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Ballou, D.P., Wang, R.Y., Pazer, H., & Tayi, G.K. (1997). Modelling information manufacturing systems to determine information product quality. Management Science, 44 (4), 462-484.
2. Deming, E.W. (1986). Out of the Crisis. Center for Advanced Engineering Study, MIT, Cambridge, MA.
3. Doggett, A.M. (2005). Root cause analysis: A framework for tool selection. QualityManagement Journal, 12 (4), 34-45.
4. Garvin, (1988). Managing Quality: The strategic and Competitive Edge. Free Press, New York.
5. Gurbaxani, V. & Wang, S. (1991). The impact of information systems on organizations and markets. Communications of the ACM, 34 (1), 59-73.
6. Hevner, A.R.; March, S.T.; Park, J.; Ram, S. (2004). Design Science in Information Systems Research, MIS Quarterly 28 (1), 75-105.
7. Kovac, R., Lee, Y.W., & Pipino, L.L. (1997). Total Data QualityManagement: the case of IRI. Proceedings of the Conference on Information Quality, pp. 63-79.
8. Mintzberg, H. (1983). Structures in fives: Designing effective organizations. Prentice-Hall, Englewood Cliffs (NJ).
9. Moore, D.S. & McCabe, G.P. (1989). Introduction to the Practice of Statistics.W.H. Freeman Company, London.
10. Pipino, L.L., Lee, Y.W., & Wang, R.Y. (2002) Data quality assessment. Communications of the ACM, 45 (4), 211-218.
11. Poston, R. & C. Speier (2005), Effective use of knowledge management systems: A process model of content ratings and credibility indicators. Management Information Systems Quarterly, 29 (2), 221-244.
12. Redman, T. C. (1998). The impact of poor data quality on the typical enterprise. Communications of the ACM, 41 (2), 79-82.
13. Romme, A.G. (2003), Making a difference: Organization as design. Organization Science, 14 (5), 558-573.
14. Stamper, R. (1973), Information in business and administrative systems. JohnWiley, New York.
15. Sveiby, K.E. (1997). The new organizational wealth: Managing and measuring knowledge-based assets. Berrett-Koechler, San Francisco (CA).
16. Te'eni, D. (2001), Review: A cognitive-affective model of organizational communication for designing IT. Management information systems quarterly, 25 (2), 251-312.
17. Van Aken, J.E. (2004). Management Research Based on the Paradigm of the Design Sciences: The Quest for Field-Tested and Grounded Technological Rules. Journal ofManagement Studies, 41 (2), 219-246.
18. Venkatraman, N. & Henderson, J.C. (1998). Real Strategies for Virtual Organizing. Sloan Management Review, 41 (1), 33-48.
19. Walls, J.G., G.R. Widmeyer, & O.A. El Sawy (1992). Building an information system design theory for vigilant EIS. Information Systems Research, 3 (1), 36-59.
20. Wang, R.Y. (1998). A product perspective on total data quality management. Communications of the ACM, 41 (2), 58-65.
21. Wang, R. Y. & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12 (4), 5-34.
22. Zahedi, F. (1995). Quality Information Systems. Boyd & Fraser, Danvers (MA).