The Expert Systems Life Cycle in AIS Research: What it Means for Future AIS Research 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 University of Waterloo Symposium on Information Integrity & Information Systems Assurance 8 th Biennial Research Symposium October 4-5, 2013

 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

 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

Publications

 RQ1: Did expert systems research in accounting and AIS domain go through a similar industry life cycle over time?  RQ2: Did the type of research evolve over time as would be predicted by the industry life cycle and the Gartner hype curve?  RQ3: Did the type of researcher evolve 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?

 Search electronic literature databases AI/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]

 Dedication…  Paul Steinbart develops expert system at night at community college because MSU doesn’t have appropriate DEC VAX computer. [ ]  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]

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

Total = 233 articles

Top Journals with the Most Expert Systems PublicationsCount% 1 Expert Systems with Applications % 2 Auditing: A Journal of Practice & Theory156.44% 3 Journal of Information Systems146.01% 4 New Review of Applied Expert Systems and Emerging Technologies93.86% 5 Accounting Education83.43% 6 Accounting, Organizations and Society62.58% 7 International Journal of Accounting Information Systems62.58% 8 Intelligent Systems in Accounting, Finance & Management62.58% 38.64%

PUBLICATIONS BY ACCOUNTING AREA

CHANGING MIX OF APPLICATION AREAS

DISTRIBUTION OF AUTHORSHIPS Number of Articles Published Number of AuthorsPercent of Authors % % % % % %

Top Expert Systems AuthorsPublications% 1 Carol E. Brown 73.00% 2 Daniel E. O’Leary 73.00% 3 Robert H. Michaelsen 62.58% 4 Alan Sangster 62.58% 5 Mary Ellen Phillips 52.15% 6 Mohammad J. Abdolmohammadi 41.72% 7 Andrew D. Bailey, Jr % 8 Amelia Annette Baldwin-Morgan 41.72% 9 Martha M. Eining 41.72% 10 James V. Hansen 41.72% 11 Clyde W. Holsapple 41.72% 12 R. Steve McDuffie 41.72% 13 David S. Murphy 41.72% 14Paul J. Steinbart41.72%

EXPERT SYSTEMS DISSERTATIONS

AAA MEETING PRESENTATIONS YearPresentation # Pre-1998(Being compiled)

1. Being first to embrace a new technology limits the types of research, but it also provides some freedom. 2. Being in the lead (ahead of practice) is a prized position. 3. It is hard to lead if no one is following. 4. If academics do a good job of leading practice, practice eventually will take the lead.

5. 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. 6. 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.

7. 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. 8. More?