Diagnostic and functional dependencies of credibility

Informing Science

Volumn 9, Issue , 2006, Pages 225-241

  Gackowski, Zbigniew J ^a  

^a CALIFORNIA STATE UNIVERSITY   (United States)

Author keywords

Actionable credibility of informing; Operation quality of information

Indexed keywords

EID: 33845361321     PISSN: 15214672     EISSN: 15214672     Source Type: Journal    
DOI: 10.28945/481     Document Type: Article

References (13)

1. Financial Accounting Standard Board [FASB]. (1983). Accounting standard: Statement of financial accounting concepts. New York, NY: McGraw-Hill.
2. Gackowski, Z. J. (2004). Logical interdependence of data/information quality dimensions - A purpose-focused view on IQ, Proceedings of the Ninth International Conference on Information Quality (ICIQ-04), Cambridge, Massachusetts. Retrieved from http://www.iqconference.org/Documents/IQ Conference 2004/Papers/LogicalInterdependence.pdf
3. Gackowski, Z. J. (2005a). Informing systems in business environment: A purpose-focused view. Informing Science Journal, 8, 101-122. Retrieved June 27,2005, from http://infom.nu/Articles/Vol8/v8p101-122Gack.pdf
4. Gackowski, Z. J. (2005b). Operation quality of data and information: Teleological operations research-based approach, call for discussion. Proceedings of the 10th Anniversary International Conference on Information Quality - ICIQ-05, Massachusetts Institute of Technology (MIT), Cambridge, MA
5. th International Conference on Information Quality (ICIQ-05), Cambridge, Massachusetts.
6. Gleim, I. N. (2004). CPA Review Financial (12th ed.;. Gleim Publications.
7. Huang, K., Lee, Y. W., & Wang, R. Y. (1999). Quality information and knowledge. Upper Saddle River, NJ: Prentice Hall (Quality Programs and Initiatives at MIT-MITIQ Program.)
8. Information system. (2005). Encyclopedia Britannica. Retrieved April 22, 2005, from Encyclopedia Britannica Online http://search.eb.com/eb/article?tocId= 21.8074
9. Lee, Y., Strong, D., Kahn, B., & Wang, R. (2002). AIMQ: A methodology for information quality assessment. Information & Management, 40(2), 133-146. Retrieved from http://mitiq.mit.edu/Documents/Publications/TDOMpub/ 2002/AIMO.pdf
10. Liu, L., & Chi, L. N. (2002). Evolutional data quality: A theory-specific view. Proceedings of the Seventh International Conference on Information Quality (ICIQ-02), Cambridge, Massachusetts, 292-304. Retrieved, from http://www.iqconference.org/iciq/iqdownload.aspx?ICIQYear=2002&File= EvolutionalDataQualityATheorySpecificView.pdf
11. Wand, Y., & Wang R. Y. (1996). Anchoring data quality dimensions in ontological foundations. Communications of the ACM, 39(11), 86-95. Retrieved, from https://www.crg2.com/iqconference/documents/publications/TDOMpub/ WandWangCACMNov96.pdf
12. Wang, R. Y., Reddy, M. P., & Kon, H. B. (1995). Toward quality data: An attribute-based approach, Journal of Decision Support Systems, 13, 349-372.
13. Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems (JMIS), 12(4), 5-34. Retrieved, from http://jmis.bentley.edu/articles/v12_n4_p5/ index.html