The Impact of System and Data Quality on Organizational Success in the Kingdom of Bahrain

Authors: Amal M. Alrayes

Abstract:

Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance. Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: Data quality, performance, system quality.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1105421

References:

[1] S.S. Cherfiand G. Poels. “Information quality, system quality and information system effectiveness: Introduction to QoIS06”, in Advances in conceptual modeling: Theory and practice, V.R. Benjaminsand J.F. Roddick, Eds. Berlin: Springer, 2006, pp. 325-328.
[2] B. Baesens, K. Dejaeger, W. Lemahieu and H. Moges, “A multidimensional analysis of data quality for credit risk management: New insights and challenges”, Information & Management, vol. 50, pp. 43-58, 2013.
[3] Data Management Association, “Data quality dimensions”, DAMA UK Working Group (October 2013) pp. 13.
[4] Couture, N. (2013) ‘Implementing an Enterprise Data Quality Strategy’, Business Intelligence, 18(4), pp. 46-51.
[5] Lee, Y.W, Madnick, S.E., Wang, R.Y. and Zhu, H. (2012). Data and Information Quality Research: Its Evolution and Future, CRC: Chapman & Hall.
[6] DeLone, W.H. and McLean, E.R. (2003) The DeLone and McLean model of information system success. Journal of Management Information System 19, 9–30.
[7] Eddon, P.B. (1997). A respecification and extension of the Delone and McLean model of IS success. Information Systems Research, 240, pp.240–253.
[8] Gorla, N., Somers, T.M. and Wong, B. (2010). Organizational Impact of System Quality, Information Quality, and Service Quality, Journal of Strategic Information Systems, 19(3), pp. 207-228.
[9] D. Sedera and G. Gable, “A factor and structural equation analysis of the enterprise systems success measurement model” in Proceedings of the Twenty-Fifth International Conference on Information Systems. Association for Information Systems, Washington, DC, 2004 p. 449.
[10] IEEE. (1992). “IEEE Standard for a Software-Quality Metrics Methodology.” IEEE Std 1061-1992. 1992. Institute of Electrical and Electronics Engineers, New York, NY.
[11] Clements, P., Bachmann, F., Bass, L., Garlan, D., Ivers, J., Little, R., Nord, R., and Stafford, J. (2002). Documenting Software Architectures: Views and Beyond, Addison Wesley.
[12] Batini, C., Cappiello, C., Francalanci, C., and Maurino, A. (2009) Methodologies for data quality assessment and improvement. ACM Computing Surveys. 41(3), 123-174.
[13] Indulska, M., Sadiq, S. and Yeganeh, N. K. (2011). 20 years of data quality research: Themes, trends and synergies. In Twenty-Second Australasian Database Conference
[ADC]. Perth, WA, Australia, January 2011. Sydney, NSW, Australia: Australian Computer Society, pp. 1-10.
[14] Redman, T. C. (2000). Data Quality. Digital Press: Boston.
[15] Gretchen Rickards, Charles Magee, and Anthony R. Artino, Jr (2012) You Can't Fix by Analysis What You've Spoiled by Design: Developing Survey Instruments and Collecting Validity Evidence. Journal of Graduate Medical Education: December 2012, Vol. 4, No. 4, pp. 407- 410.
[16] Shannon, C.E., and Weaver, W. (1949). The Mathematical Theory of Communication, Urbana, University of Illinois Press.
[17] Marschak, J., and Radner, R. (1972) Economic Theory of Teams. Yale University Press, New Haven.
[18] Feltham, G. The value of information. Account. Rev. 43, 4 (1968), pp. 684–696.
[19] Batini, R. and Scannapieca, M. (2006) Data Quality: concepts, methodologies and techniques, USA, Springer.
[20] Sagor, R, (2009).Guiding school improvement with Action Research.
[21] Braverman, M.T., & Engle, M. (2009). Theory and rigor in Extension program evaluation planning. Journal of Extension (Online), 47(3), Article 3FEA1. Available at: http://www.joe.org/joe/2009june/a1.php
[22] Sebastian-Coleman, L. (2013) Measuring DataQuality for Ongoing Improvement: A Data Quality Assessment Framework, 1 edn., USA: Morgan Kaufmann.
[23] Lee, Y.W, Madnick, S.E., Wang, R.Y. and Zhu, H. (2009) ‘Overview and Framework for Data and Information Quality Research’, ACM Journal of Data and Information Quality, 1(1), pp. 23-44.
[24] Fisher, C. W., & Kingma, D. R. (2001). Criticality of Data Quality as examplified in two disasters. Information & Management, 39, 109-116.
[25] Strong, D.M. and Wang, R.Y. (1996). Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems, 12, 5–34.
[26] Jung, W. (2004) ‘A Review of Research: An Investigation of the Impact of Data Quality on Decision Performance’, International Symposium on Information and Communication Technologies, 54(1), pp. 166 - 171.
[27] Bakos, Y.J., Treacy, M.E., 1986. Information technology and corporate strategy: a research perspective. MIS Quarterly 10, 107–119.
[28] Swanson, Maintaining IS quality. Information and Software Technology. v39. 845-850, 1997.
[29] Barbara H. Wixom , Hugh J. Watson, An empirical investigation of the factors affecting data warehousing success, MIS Quarterly, v.25 n.1, p.17-32, March 2001.
[30] Bradley, R.V., Byrd, T.A., and Pridmore, J.L. (2006) Information systems success in the context of different corporate cultural types: an empirical investigation, Journal of Management Information Systems, 23(1), 267–294.
[31] Salmela, From information system quality to sustainable business quality. Information and Software Technology. v39. 819-825, 1997
[32] Sandra A. Slaughter, Donald E. Harter, Mayuram S. Krishnan, Evaluating the cost of software quality, Communications of the ACM, v.41 n.8, p.67-73, Aug. 1998.
[33] A.A. Törn, Models of software accumulation, Journal of Systems and Software, v.12 n.1, p.39-42, Apr. 1990.
[34] Ravichandran, T. and Lertwongsatien, C. (2005). Effect of information systems resources and capabilities on firm performance: A resourcebased perspective. Journal of Management Information Systems, 21, 237–276.
[35] Gregory, R.J. (1992). Psychological testing: history, principles and applications. Boston: Allyn and Bacon
[36] DeVellis, R.F. (1991). Scale Development: theory and applications (Applied Social Research Methods Series, Vol. 26). Newbury Park: Sage.