Antonio Thonis

The past 1,5 month I had a great time following the Business Intelligence course at my university which was given in collaboration with Deloitte. We even attended a BI/recruitment session at the headquarters of IBM Netherlands. BI seems like a great field for business students with technical capabilities.

Interested in Business Intelligence, Decision Support Systems, Expert Systems, Data Warehousing and Data Mining? Here follows an overview of all the academic papers on Business Intelligence that we had to read for our exam:

• A framework for the development of Decision Support Systems, R.H. Sprague, MIS Quarterly, Volume 4, Issue 4 (Dec. 1980).
• The science, not art, of business intelligence, M.C. O’Guin, et al.,  CompetitiveIntelligence Review vol 12(4) 15-24 (2001).
• Towards real-time business intelligence, D. Azvine, Z Cui, D.D. Nauck, BT Technology Journal, Vol 23 No 3, July 2005.
• Intelligence generation and superior customer value, S.F. Slater, J.C. Narver, Journal of the Academy of Marketing Science, Vol 28 No. 1 120-127.
• Specifying an expanded framework for classifying and describing decision support systems, Daniel J. Power, Communications of the Association for information Systems, Vol. 13, 158-166 (2004)
• Competing on Analytics, Thomas H. Davenport, Harvard Business Review, January 2006.

• Integrated decision support systems: A data warehousing perspective, Salvatore T.
  March, Alan R. Hevner, Decision Support Systems, Vol. 43 (2007)
• The benefits of data warehousing: Why some organizations realize exceptional payoffs, H.J.Watson, et al., Information & Management 39 (2002) 491-502.
• Data Warehousing Supports Corporate Strategy At First American Corportation, Brian L. Cooper et al., MIS Quarterly Vol. 24 No. 4, pp. 547-567/December 2000
• An overview of data warehousing and OLAP technology, S. Chauduri & U. Dayal.
  Paragraph 6 is not mandatory, reading this paragraph will be sufficient.
• Building the data warehouse, Stephen R. Gardner, Communications of the ACM, 41(9) (1998).

• Determining Information Requirements for an EIS, Hugh J. Watson, Mark N. Frolick, MIS Quarterly, Volume 17, Issue 3 (Spe. 1993), 255-269.
• Critical Success factors revisited: success and failure cases of information systems for senior executives, Decision Support Systems 30 (2001) 393-418.
• What does it take for successful executive information systems?, Decision Support Systems 14 (1995) 147-156.

• The evolution of expert systems., Ovidiu S. Noran,
• An introduction to Expert Systems, Michael Will, Picodoc Corporation, 2001.
• Knowledge management and data mining for marketing, M.J. Shaw, et al., Decision Support Systems 31 (2001) 127 – 137.
• From Data Mining to Knowledge Discovery in Databases; Usama Fayyad, et al., American Association for Artificial Intelligence, Fall 1996, p. 37-54.
• Assessing Loan Risks: A Data Mining Case Study, Rob Gerritsen, IT Pro, November/December 1999.

• Data to knowledge to results: Building an analytic capability, Thomas H. Davenport, et al., California Management Review Vol 43, No.2, Winter 2001.
• Evolving from Information to Insight, G. Ferguson et al., MIT Sloan Management Review, Winter 2005, vol. 46, no.2.
• Data quality in context, D.M. Strong, et al., Communications of the ACM, May 1997/Vol. 40.No.5.
• The impact of Data Integration on the Costs and Benefits of Information Systems, MIS Quarterly, September 1992, p 293-311.
• A business case framework for group support technology, Post, Brad Quinn, Journal of Management Information Systems, Winter 1992-1993, Vol. 9, iss. 3

• Management issues in data warehousing: insights from the Housing and Development Board, J. Ang & T.S.H. Teo, Decsion Support Systems 29 (2000) 11-20.
• An empirical investigation of the factors affecting data warehousing success, B.H. Wixom, H.J. Watson, MIS Quarterly, Vol. 25 no. 1, march 2001.
• An empirical investigation of the key determinants of data warehouse adoption, Ramamurthy, Sen & Sinha, Decision Suppport Systems, vol. 44 (2008) p 817-841.
• Strategic actions in information technology investment based on real option theory, Yong Jin Kim, G. Lawrence Sanders, Decision Support Systems 33 (2002) 1-11.
• The measurement of business intelligence, Lönnqvist & Pirttimäki, Information Systems Management, Vol. 23 (2006).
• Price and Value of Decision Support Systems, Dan R. Pieptea, Evan Anderson, MIS Quarterly December 1987, p515-528
• Past, present and future of decision support technology; J.P. Shim et al., Decision Support Systems 33 (2002) 111-126.
• Progress in Web-based decision support technologies, Hermant K. Bhargava, Daniel J. Power, Daewon Sun, Decision Support Systems 43 (2007) 1083-1095.

I’ve highlighted some of my favorite papers and the most important ones, enojoy!

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