A cognitive study of the decision-making process in a business context: implications for design of expert systems

Abstract Problem-solving in the business domain differs considerably from the traditional domains such as physics, cryptarithmetic etc. that are normally used in psychological experiments. The use of qualitative data, personal judgment, and experiential learning results in considerable ambiguity in the problem representation and solution strategy. A cognitive study of the decision-making process in the business domain was conducted and the results indicated that there were differences between subjects in problem representation and solution strategies. The reasons for these differences were analysed and the implications of these findings on the design of expert system were evaluated.

[1]  Paul J. Feltovich,et al.  Categorization and Representation of Physics Problems by Experts and Novices , 1981, Cogn. Sci..

[2]  Jack W. Fellers,et al.  Skills and Techniques for Knowledge Acquisition: a Survey, Assessment, and Future Directions , 1987, ICIS.

[3]  Clive L. Dym,et al.  Knowledge Acquisition from Multiple Experts , 1984, AI Mag..

[4]  Herbert A. Simon,et al.  Understanding written problem instructions. , 1974 .

[5]  John P. McDermott,et al.  R1: A Rule-Based Configurer of Computer Systems , 1982, Artif. Intell..

[6]  H. Simon,et al.  The functional equivalence of problem solving skills , 1975, Cognitive Psychology.

[7]  W MaloneThomas,et al.  Expert systems: the next challenge for managers , 1986 .

[8]  Walter G. Rolandi.  Knowledge engineering in practice , 1986 .

[9]  Jan H. B. M. Huysmans,et al.  The Effectiveness of the Cognitive-Style Constraint in Implementing Operations Research Proposals , 1970 .

[10]  Stephen F. Smith,et al.  ISIS—a knowledge‐based system for factory scheduling , 1984 .

[11]  David S. Prerau.  Selection of an Appropriate Domain for an Expert System , 1985, AI Mag..

[12]  G. A. Miller.  THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[13]  Paul R. Cohen,et al.  A Report on FOLIO: An Expert Assistant for Portfolio Managers , 1983, IJCAI.

[14]  Marinus J. Bouwman.  Human Diagnostic Reasoning by Computer: An Illustration from Financial Analysis , 1983 .

[15]  H. Simon,et al.  Perception in chess , 1973 .

[16]  Herbert A Simon,et al.  The understanding process: Problem isomorphs , 1976, Cognitive Psychology.

[17]  Nicholas P. Vitalari,et al.  Knowledge as a Basis for Expertise in Systems Analysis: An Empirical Study , 1985, MIS Q..

[18]  M. L. Bariff,et al.  Cognitive and Personality Tests for the Design of Management Information Systems , 1977 .

[19]  Edward J. Lusk,et al.  Human information processing research: Its MIS-design consequences , 1982 .

[20]  Izak Benbasat,et al.  Behavioral Aspects of Information Processing for the Design of Management Information Systems , 1982, IEEE Transactions on Systems, Man, and Cybernetics.

[21]  Lefcourt Hm,et al.  Recent developments in the study of locus of control. , 1972 .

[22]  Thomas W. Malone,et al.  Expert systems: the next challenge for managers , 1986 .

[23]  K. A. Ericsson,et al.  Verbal reports as data. , 1980 .

[24]  R. Zmud.  INDIVIDUAL DIFFERENCES AND MIS SUCCESS: A REVIEW OF THE EMPIRICAL LITERATURE* , 1979 .

[25]  H A Simon,et al.  The theory of learning by doing. , 1979, Psychological review.

[26]  Herbert A. Simon,et al.  Problem Solving in Semantically Rich Domains: An Example from Engineering Thermodynamics , 1977, Cogn. Sci..

[27]  H A Simon,et al.  How Big Is a Chunk? , 1974, Science.

[28]  Ronald N. Taylor.  Age and Experience as Determinants of Managerial Information Processing and Decision Making Performance , 1975 .

[29]  Vasant Dhar,et al.  On the Plausibility and Scope of Expert Systems in Management , 1985, J. Manag. Inf. Syst..

[30]  Jay F. Nunamaker,et al.  A Knowledge Based Approach for Resource Management , 1987, ICIS.

[31]  Dorothea P. Simon,et al.  Expert and Novice Performance in Solving Physics Problems , 1980, Science.

[32]  B. K. Blaylock,et al.  COGNITIVE STYLE AND THE USEFULNESS OF INFORMATION , 1984 .

[33]  G. Huber.  Cognitive Style as a Basis for MIS and DSS Designs: Much ADO About Nothing? , 1983 .