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Glen L. Gray California State University, Northridge Victoria Chiu SUNY New Paltz

University of Waterloo Symposium on Information Integrity & Information Systems Assurance 8 th  Biennial Research Symposium. Glen L. Gray California State University, Northridge Victoria Chiu SUNY New Paltz Qi Liu and Pei Li Rutgers University, The State University of New Jersey.

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Glen L. Gray California State University, Northridge Victoria Chiu SUNY New Paltz

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  1. University of Waterloo Symposium on Information Integrity & Information Systems Assurance8th Biennial Research Symposium Glen L. Gray California State University, Northridge Victoria Chiu SUNY New Paltz Qi Liu and Pei Li Rutgers University, The State University of New Jersey • October 4-5, 2013

  2. Sutton (2005) The role of AIS research in guiding practice. • AIS research more applied research vs. basic research, putting AIS researchers at a disadvantage in terms of publication outlets. • Alles, Kogan, Vasarhely (2008) Exploiting comparative advantage… • AIS researchers face more competition compared to NAIS… • Researchers in: IS, IT, CS, EE, plus others • Accounting firms • Other technology organizations Background -- General

  3. O’Leary (2008) Gartner's Hype Cycle and Information System Research Issues and (2009) The Impact of Gartner's Maturity Curve, Adoption Curve, Strategic Technologies on Information Systems Research... Moore (2002) Crossing the Chasm Background – AIS/AI/Es

  4. Garner Hype Curve

  5. Product (or Research) Life Cycle

  6. Researcher Groups Publications

  7. Chasms

  8. RQ1: Did expert systems research in accounting and AIS domain go through a similar industry life cycle over time? RQ2: Did the type of researchevolve over time as would be predicted by the industry life cycle and the Gartner hype curve? RQ3: Did the type of researcherevolve over time as would be predicted by the adoption life cycle? RQ4: Did the evolution of the type researcher encounter chasms that slowed or stopped expert system research as would be predicted by Moore? Research Questions

  9. Search electronic literature databasesAI/ES/KD AND Accounting/Auditing/Tax[Challenge: Searching early paper-based literature.] Interview accounting professors who had early and/or frequent hits Interview Big 4 (6/8) representatives[Challenge: finding people who remember the 80s] Reasearch Method

  10. Preliminary Results

  11. Dedication… • Paul Steinbart develops expert system at night at community college because MSU doesn’t have appropriate DEC VAX computer. [1982-84] • Serendipity… • Bob Michaelsen (author of first ES/accounting paper) included ES in his tax dissertation because his daughter was in Brownies with David Waltz’s daughter. [1979…] • Tenacious… • Called ES companies until she found a company who would give her a fully-functional ES for research. [1997] Some Great Stories…

  12. Edward Feigenbaum visits University of Turku (Finland) and talks about A.I. and Mycin-- sounds like “fun.” 1985, Barbo Back builds 500-700 rule expert system in LPA Prolog. Domain: Corporate tax: 60% Maximum, but many, many exceptions, credits, etc. Carries MAC to interview practitioners. Results… A Story to Beat

  13. RQ1: Expert Systems Publications Total = 233 articles

  14. Top Journals 38.64%

  15. RQ2: Type of Publications

  16. Publications by Accounting Area

  17. Changing Mix of Application Areas

  18. Distribution of Authorships

  19. R3/R4: Frequent Authors (Preliminary)

  20. Expert Systems Dissertations

  21. AAA Meeting Presentations

  22. Publications in other fields

  23. Being first to embrace a new technology limits the types of research, but it also provides some freedom. • Being in the lead (ahead of practice) is a prized position. • It is hard to lead if no one is following. • If academics do a good job of leading practice, practice eventually will take the lead. Lessons Learned?

  24. The Gartner hype cycle will usually catch up with researchers (what goes up, must come down). • Corollary: When in the trough of disillusionment, it’s hard to determine the trough’s length and the slope of the plateau and some researchers will leave instead of risking a long trough or a downward sloping plateau. • The types of research within a domain must evolve over time. • Corollary: Chasms will be encountered as types of research evolve—some may be impossible to cross. LeSsons Learned?

  25. The types of researchers will change as the types research progresses. • Corollary: After crossing each chasm, some current researchers will leave and new researcher will join the domain. • More? Lessons Learned?

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