An empirical comparison of utility assessment programs

Abstract This paper reports on an experimental investigation of the utility functions elicited by four different utility elicitation computer programs. We were able to confirm that decision making subjects will to a degree follow the recommendation of a utility elicitation program in contravention to the subject's intuitive judgments of preference. Further, we found systematic differences in this regard among the four programs. Programs that confront subjects with their inconsistencies and force a reworking of the subject's expressed preferences appear to produce utility functions with greater acceptance by decision makers. Similarly, programs that employ a direct manipulation style of interface also appear to result in greater acceptance by subjects of the utility functions elicited.

[1]  J. Neumann,et al.  Theory of Games and Economic Behavior. , 1945 .

[2]  Sirkka L. Jarvenpaa,et al.  Computer support of groups: theory-based models for GDSS research , 1991 .

[3]  P. Schoemaker,et al.  Probability Versus Certainty Equivalence Methods in Utility Measurement: Are they Equivalent? , 1985 .

[4]  N. Melone.  A theoretical assessment of the user-satisfaction construct in information systems research , 1990 .

[5]  Gerardine DeSanctis,et al.  A foundation for the study of group decision support systems , 1987 .

[6]  Ben Shneiderman,et al.  The future of interactive systems and the emergence of direct manipulation , 1982 .

[7]  Brian L. Dos Santos,et al.  A Study of User Interface Aids for Model-Oriented Decision Support Systems , 1988 .

[8]  Ramesh Sharda,et al.  Decision support system effectiveness: a review and an empirical test , 1988 .

[9]  Starr Roxanne Hiltz,et al.  User satisfaction with computer-mediated communication systems , 1990 .

[10]  Richard A. Bolt,et al.  The human interface: Where people and computers meet , 1984 .

[11]  Peter C. Fishburn,et al.  Nonlinear preference and utility theory , 1988 .

[12]  Ben Shneiderman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction , 1998 .

[13]  H. Kunreuther,et al.  Decision Making: SOURCES OF BIAS IN ASSESSMENT PROCEDURES FOR UTILITY FUNCTIONS , 1982 .

[14]  P. Farquhar.  State of the Art—Utility Assessment Methods , 1984 .

[15]  Richard S. John,et al.  The Quality and User Acceptance of Multiat-Tribute Utility Analysis Performed by Computer and Analyst , 1983 .

[16]  P. Humphreys,et al.  Experiences with MAUD: Aiding decision structuring versus bootstrapping the decision maker☆ , 1980 .

[17]  Mark R. McCord,et al.  Lottery Equivalents: Reduction of the Certainty Effect Problem in Utility Assessment , 1986 .

[18]  Robert de Hoog,et al.  Non-Expert Use of a Computerized Decision Aid1 , 1983 .

[19]  Martin Weber.  Decision Making with Incomplete Information , 1987 .

[20]  Daniel J. Power,et al.  AN EMPIRICAL ASSESSMENT OF COMPUTER‐ASSISTED DECISION ANALYSIS* , 1986 .

[21]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[22]  James D. Hollan,et al.  Direct Manipulation Interfaces , 1985, Hum. Comput. Interact..

[23]  Martin Weber,et al.  Utility function assessment on a micro-computer: An interactive procedure , 1988 .

[24]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[25]  Colin Camerer,et al.  Recent developments in modelling preferences under risk , 1987 .

[26]  L. Robin Keller,et al.  Empirical investigation of some properties of the perceived riskiness of gambles , 1986 .

[27]  Martin Weber,et al.  Utility Function Assessment on a Micro-Computer: A Reliable, Interactive Procedure , 1988 .

[28]  M. Allais.  Le comportement de l'homme rationnel devant le risque : critique des postulats et axiomes de l'ecole americaine , 1953 .

[29]  Ben Shneiderman,et al.  Direct Manipulation: A Step Beyond Programming Languages , 1983, Computer.