An Evolutionary Approach to Group Decision Making

References

• Aytug H., Koehler G. J. Stopping criteria for finite length genetic algorithms. ORSA Journal on Computing (1996) 8:183–191Link, Google Scholar
• Aytug H., Koehler G. J. New stopping criteria for genetic algorithms. European Journal of Operational Research (2000) 126:662–674Crossref, Google Scholar
• Barkhi R. An empirical study of the impact of proximity, leader and incentives on negotiation process and outcomes in a group decision support setting. (1995) . Doctoral dissertation, Department of Decision Sciences and Information Systems, The Ohio State University, Columbus, OHGoogle Scholar
• Bhattacharyya S., Koehler G. J. An analysis of genetic algorithms of cardinality 2V. Complex Systems (1994) 8:227–256Google Scholar
• Chidambaram L., Bostrom R. P., Wynne B. E. A longitudinal study of the impact of group decision support systems on group development. Journal of Management Information Systems (1991) 7:7–25Crossref, Google Scholar
• De Jong K. A., Spears W. M., Gordon D. F. Using Markov chains to analyze GAFOs. Foundations of Genetic Algorithms 3 (1995) (Morgan Kaufmann, San Francisco, CA) 115–137Crossref, Google Scholar
• DeSanctis G., Gallupe R. B. A foundation for the study of group decision support systems. Management Science (1987) 33:589–609Link, Google Scholar
• Gallupe R. B., DeSanctis G. Computer-based support for group problem-finding: an experimental investigation. MIS Quarterly (1988) 12:277–296Crossref, Google Scholar
• Gavish B., Kalvenes J., Pirkul H., Shaw M. Economic issues in group decision support systems. Proceedings of the First INFORMS Conference on Information Systems and Technology (1996) (INFORMS, Washington, DC) 18–27Google Scholar
• Goldberg D. E.Genetic Algorithms in Search, Optimization, and Machine Learning (1989) (Addison Wesley, Reading, MA) Google Scholar
• Gopal A., Bostrom R. P., Chin W. W. Applying adaptive structuration theory to investigate the process of group support systems use. Journal of Management Information Systems (1993) 9:45–69Crossref, Google Scholar
• Guzzo R. A., Dickson M. W., Spence J. T., Darley J. M., Foss D. J. Teams in organizations: recent research on performance and effectiveness. Annual Review of Psychology (1996) 47:307–338Crossref, Google Scholar
• Hiltz S. R. Productivity enhancement from computer-mediated communications: a systems contingency approach. Communications of the ACM (1988) 31:1438–1454Crossref, Google Scholar
• Hirokawa R., Johnson D. Toward a general theory of group decision making development of an integrated model. Small Group Behavior (1989) 20:500–523Crossref, Google Scholar
• Koehler G. J. Computing simple GA expected waiting time. Genetic and Evolutionary Computation Conference (1999) (Morgan Kauf-mann, Orlando, FL, 795) Google Scholar
• Koehler G. J., Bhattacharyya S., Vose M. D. General cardinality genetic algorithms. Evolutionary Computation (1998) 5:439–459Crossref, Google Scholar
• Mood A. M.Introduction to the Theory of Statistics (1950) (McGraw-Hill, New York) Google Scholar
• Nunamaker J. F., Dennis A. R., Valacich J. S., Vogel D. R., George J. F. Electronic meeting systems to support group work. Communications of the ACM (1991) 34:40–61Crossref, Google Scholar
• Poole M. S., DeSanctis G., Steinfeld C. W., Fulk J. Understanding the use of group decision support systems: the theory of adaptive structuration. Organizations and Communication Technology (1990) (Sage Press, Newbury Park, CA) 173–193Crossref, Google Scholar
• Rao V. S., Jarvenpaa S. L. Computer support of groups: theory-based models for GDSS research. Management Science (1991) 37:1347–1362Link, Google Scholar
• Rees J., Barkhi R. The problem of highly constrained tasks in group decision support systems. European Journal of Operational Research (2001) 135:220–229Crossref, Google Scholar
• Rees J., Koehler G. J., Davis D., De Jong K., Vose M., Whitley D. An investigation of GA performance results for different cardinality alphabets. IMA Volumes in Mathematics and its Applications Proceedings from the IMA Workshop on Evolutionary Algorithms (1998) (Springer, New York) Google Scholar
• Rees J., Koehler G. J. Brainstorming, negotiating and learning in group decision support systems: an evolutionary approach. Proceedings from the Thirty-Second Annual Hawaii International Conference on System Sciences (1999) (IEEE Computer Society Press, Los Alamitos, CA) Crossref, Google Scholar
• Shamir B. Calculations, values, and identities: the sources of collectivistic work motivation. Human Relations (1990) 43:313–332Crossref, Google Scholar
• Siegel S.Nonparametric Statistics for the Behavioral Sciences (1956) (McGraw-Hill, New York) Google Scholar
• Steiner I. D. Models for inferring relationships between group size and potential group productivity. Behavioral Science (1966) 11:273–283Crossref, Google Scholar
• Steiner I. D.Group Process and Productivity (1972) (Academic Press, New York) Google Scholar
• Valacich J. S., Dennis A. R. A mathematical model of performance of computer-mediated groups during idea generation. Journal of Management Information Systems (1994) 11:59–72Crossref, Google Scholar
• Vose M. D. Formalizing genetic algorithms. Proceedings of the IEEE Workshop on Genetic Algorithms, Neural Networks, and Simulated Annealing Applied to Signal and Image Processing (1990) (Sinauer Associates, Glasgow, Scotland) 212–232Google Scholar
• Vose M. D.The Simple Genetic Algorithm: Foundations and Theory (1999) (MIT Press, Cambridge, MA) Crossref, Google Scholar
• Vose M. D., Liepins G. E. Punctuated equilibria in genetic search. Complex Systems (1991) 5:31–44Google Scholar
• Vose M. D., Wright A. H. Simple genetic algorithms with linear fitness. Evolutionary Computation (1995) 2:347–368Crossref, Google Scholar
• Watson R. T., DeSanctis G., Poole M. S. Using a GDSS to facilitate group consensus: some intended and unintended consequences. MIS Quarterly (1988) 12:463–477Crossref, Google Scholar