The debiasing role of group support systems: an experimental investigation of the representativeness bias

Past research has demonstrated that individual and group judgments are subject to systematic biases. Although much effort has been devoted to the debiasing of individual judgments, no corresponding work has been found on the debiasing of group judgments. This study examines the usefulness of a group support system (GSS) in addressing an important judgment bias, namely, the representativeness bias, which refers to the bias incurred in posterior-probability estimations by not properly utilizing all information sources, such as the base rates.The formation of a judgment is seen from the perspective of an information integration process. Two orthogonal dimensions of information integration?interpersonalandintrapersonal?are involved in group judgments. Interpersonal information integration concerns the aspect of information sharing among group members, and can be supported with the computer-mediated communication channel of GSS. Intrapersonal information integration deals with the information processing capacities and capabilities of individuals, and can be supported using a problem representation tool, as part of GSS.A laboratory experiment with a 2×2 factorial design was conducted. One hundred and twenty subjects, randomly allocated to 40 three-member groups, took part in the experiment. Data pertaining to both processes and outcomes were collected and analysed. Representativeness bias was reduced by the use of the problem representation tool. Increased use of the tool led to greater awareness about the base rate and, consequently, to better judgments in this problem context. On the other hand, computer-mediated communication did not reduce the representativeness bias. Although computer-mediated communication is capable of improving the interpersonal aspect of information integration, the representativeness bias is primarily a result of cognitive limitations, and benefits little from improved communication among group members. It is also possible that benefits of computer-mediated communication can be more readily derived by larger groups than by smaller groups of size three used in this study.

[1]  G. Huber.  The Nature and Design of Post-Industrial Organizations , 1984 .

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

[3]  L. Beach,et al.  Experience and the base-rate fallacy. , 1982, Organizational behavior and human performance.

[4]  Linda Argote,et al.  Individual versus group use of base-rate and individuating information , 1986 .

[5]  M. E. Shaw.  A comparison of individuals and small groups in the rational solution of complex problems. , 1932 .

[6]  Y. Trope,et al.  The effects of base rates and individuating information on judgments about another person , 1980 .

[7]  D. Medin,et al.  The role of theories in conceptual coherence. , 1985, Psychological review.

[8]  Kailas Nath Tripathi.  Effect of Contingency and Timing of Reward on Intrinsic Motivation. , 1991, The Journal of general psychology.

[9]  R. Rice.  Task Analyzability, Use of New Media, and Effectiveness: A Multi-Site Exploration of Media Richness , 1992 .

[10]  Gary L. Wells,et al.  Naive Attributors' Attributions and Predictions: What Is Informative and When Is an Effect an Effect? , 1978 .

[11]  W. A. Scott,et al.  Reliability of Content Analysis ; The Case of Nominal Scale Cording , 1955 .

[12]  L. R. Hoffman.  Group Problem Solving1 , 1965 .

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

[14]  Robyn M. Dawes,et al.  Representative thinking in clinical judgment , 1986 .

[15]  A. Tversky,et al.  On the psychology of prediction , 1973 .

[16]  Nancy Paule Melone,et al.  Conservatism revisited: Base rates, prior probabilities, and averaging strategies , 1996, Behavioral and Brain Sciences.

[17]  W G Cole,et al.  Three Graphic Representations to Aid Bayesian Inference , 1988, Methods of Information in Medicine.

[18]  A. Tversky,et al.  Evidential impact of base rates , 1981 .

[19]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[20]  Marie Christine Roy,et al.  Overcoming Ineffective Mental Representations in Base-Rate Problems , 1996, Inf. Syst. Res..

[21]  G. W. Hill.  Group versus individual performance: are n + 1 heads better than one?" psychological bulletin , 1982 .

[22]  Amiram D. Vinokur,et al.  Review and theoretical analysis of the effects of group processes upon individual and group decisions involving risk. , 1971 .

[23]  Alexander Pollatsek,et al.  Understanding conditional probabilities , 1987 .

[24]  Nancy Paule Melone,et al.  The base-rate fallacy : contrasting processes and outcomes of group and individual judgment , 1990 .

[25]  Maya Bar-Hillel,et al.  The Base Rate Fallacy Controversy , 1983 .

[26]  Robert D. McPhee,et al.  Group decision‐making as a structurational process , 1985 .

[27]  Jay F. Nunamaker,et al.  Electronic meeting systems , 1991, CACM.

[28]  R. Hogarth.  Judgement and choice: The psychology of decision , 1982 .

[29]  G. Keppel,et al.  Design and Analysis: A Researcher's Handbook , 1976 .

[30]  M. Bar-Hillel.  The base-rate fallacy in probability judgments. , 1980 .

[31]  Kaoru Ono,et al.  Group Consensus Processes on Cognitive Bias Tasks: A Social Decision Scheme Approach , 1988 .

[32]  William G. Cole,et al.  Understanding Bayesian reasoning via graphical displays , 1989, CHI '89.

[33]  D. Eddy.  Judgment under uncertainty: Probabilistic reasoning in clinical medicine: Problems and opportunities , 1982 .

[34]  Izak Benbasat,et al.  A Framework for Addressing Group Judgment Biases with Group Technology , 1996, J. Manag. Inf. Syst..

[35]  A. Tversky,et al.  Causal Schemata in Judgments under Uncertainty , 1982 .

[36]  John W. Payne,et al.  Task complexity and contingent processing in decision making: An information search and protocol analysis☆ , 1976 .

[37]  Gerardine DeSanctis,et al.  Group decision support systems: a new frontier , 1984, DATB.

[38]  R. Birdwhistell.  Kinesics and context , 1970 .

[39]  I. Benbasat,et al.  The Effects of Group, Task,Context, and Technology Variables on the Usefulness of Group Support Systems , 1993 .

[40]  N. Maier.  Assets and liabilities in group problem solving: the need for an integrative function. , 1967, Psychological review.

[41]  Max Henrion,et al.  Explanation of bayesian conditioning for decision support systems , 1989 .

[42]  George P. Huber,et al.  Issues in the Design of Group Decision Support Systems , 1984, MIS Q..

[43]  John Short,et al.  The social psychology of telecommunications , 1976 .

[44]  Izak Benbasat,et al.  A Theoretical Perspective of Negotiation Support Systems , 1992, J. Manag. Inf. Syst..

[45]  Kishore Sengupta,et al.  Cognitive Feedback in GDSS: Improving Control and Convergence , 1993, MIS Q..

[46]  Harvey J. Brightman,et al.  Nominal and Interacting Groups as Bayesian Information Processors , 1983 .

[47]  Alan R. Dennis,et al.  A Meta-Analysis of Effectiveness, Efficiency, and Participant Satisfaction in Group Support Systems Research , 1996, ICIS.

[48]  A. Vinokur,et al.  Persuasive argumentation and social comparison as determinants of attitude polarization , 1977 .

[49]  Gerd Gigerenzer,et al.  Presentation and content: The use of base rates as a continuous variable. , 1988 .