Group Decision and Negotiation

, Volume 25, Issue 1, pp 127–155 | Cite as

The Evolution of Certainty in a Small Decision-Making Group by Consensus

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Abstract

We propose a dynamical systems model for approximating the certainty as a function of communication. Uncertainty is measured during a small group decision-making process, in which participants aim to reach consensus. Assuming that the communication is a one-dimensional continuum variable, both first- and second-order differential models of certainty are analyzed, and then, the general model is obtained by superposition. An experiment was organized, and the data have been used to test the model. A detailed discussion on the assumptions of this approach from the decision theory point of view is also included.

Keywords

Subjective certainty Communication Group decision-making Dynamical systems Evolution of certainty 

Notes

Acknowledgments

I would like to thank Cătălin Zamfir for the helpful discussions and for facilitating and encouraging the experimental process. I am also indebted to Cosmin Toth for encouraging this project in the first place and for participating in many helpful discussions. Also I am indebted to Adrian Duşa for helpful comments on earlier manuscripts of this paper. I would like to thank Aurelian Gheondea for his help with using MATLAB. Many thanks as well to Sorin Costiner for pointing me toward bootstrapping methodology. I am also grateful to the anonymous reviewers at GDN for the constructive feed-back that helped in considerably improving the presentation of this research.

References

  1. Beck N, Katz J (1995) What to do (and not to do) with time-series cross-section data. Am Polit Sci Rev 89(3):634–647CrossRefGoogle Scholar
  2. Beck N, Katz J (2007) Random coefficient models for time-series-cross-section data: Monte Carlo experiments. Polit Anal, 15(2):182–195. Available at: http://pan.oxfordjournals.org/cgi/doi/10.1093/pan/mpl001. Accessed Aug 2014
  3. Chadwick B, Bahr HH, Albrecht SL (1984) Social science research methods. Prentice-Hall, New JerseyGoogle Scholar
  4. Cromley RG (1982) The Von Thünen model and environmental uncertainty. Ann Assoc Am Geogr 72(3):404–410CrossRefGoogle Scholar
  5. Dean A, Voss D (1999) Design and analysis of experiments. Springer, New YorkGoogle Scholar
  6. Fiedler K, Kareev Y (2006) Does decision quality (always) increase with the size of information samples? Some vicissitudes in applying the law of large numbers. J Exp Psychol Learn Mem Cogn 32(4):883–903Google Scholar
  7. Hastie T, Tibshirani R, Friedman J (2009) Boostrap methods. In: The elements of statistical learning. Data mining, inference, and prediction, Springer, pp 252–253. Available at: http://statweb.stanford.edu/tibs/ElemStatLearn/. Accessed Aug 2014
  8. Heath C, Gonzales R (1995) Interaction with others increases decision confidence but not decision quality: evidence against information collection views of interactive decision making. Organ Behav Hum Decis Process 61(3):305–326CrossRefGoogle Scholar
  9. Hirokawa RY, Poole MS (1996) Communication and group decision making. Sage, Thousand OaksCrossRefGoogle Scholar
  10. Hirsch MW, Smale S (1974) Differential equations, dynamical systems, and linear algebra, Pure and Applied Mathematics, vol 60. Academic Press, New York-London, CambridgeGoogle Scholar
  11. Hinsz V (1999) Group decision making with responses of a quantitative nature: the theory of social decision schemes for quantities. Organ Behav Hum Decis Process, 80(1): 28–49. Available at: http://www.ncbi.nlm.nih.gov/pubmed/10508567
  12. Kahn BE, Sarin RK (1988) Modeling ambiguity in decisions under uncertainty. J Consum Res 15:265–272CrossRefGoogle Scholar
  13. Kobus DA, Proctor S, Holste S (2001) Effects of experience and uncertainty during dynamic decision making. Int J Ind Ergon 28:275–290CrossRefGoogle Scholar
  14. Laughlin PR (2011) Social choice theory, social decision scheme theory, and group decision-making. Group Process Intergroup Relat 14(1):63–79CrossRefGoogle Scholar
  15. Mann P (2010) Introductory statistics, 6th edn. Wiley, LondonGoogle Scholar
  16. Medio A, Lines M (2001) Nonlinear dynamics: a primer. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  17. Moscovici S, Doise W (1994) Conflict and consensus. Sage, LondonGoogle Scholar
  18. Niederman F, Bryson J (1998) Influence of computer-based meeting support on process and outcomes for divisional coordinating group 7:293–325Google Scholar
  19. Nøretranders T (2009/1991), Iluzia utilizatorului. Despre limitele conştiinţei [The user illusion. Cutting consciousness down to size], Publica, BucureştiGoogle Scholar
  20. Oskamp S (1982) Overconfidence in case-study judgments. In: Kahneman D, Slovic P, Tversky A (eds) Judgment under uncertainty: heuristics and biases. Cambridge University Press, New YorkGoogle Scholar
  21. Payne JW, Bettman JR, Johnson EJ (1993) The adaptive decision maker. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  22. Pedler E (2001) Sociologia comunicării [Sociology of Communication]. Syracuza Collection, Cartea Românească, BucureştiGoogle Scholar
  23. Prutianu T (2004) Antrenamentul abilităilor de comunicare [Trainning the communication abilities. Polirom, BucureştiGoogle Scholar
  24. Punchochar JM, Fox PW (2004) Confidence in individual and group decision making: when “Two Heads” are worse than one. J Educ Psychol 96(3):582–591CrossRefGoogle Scholar
  25. Robertson RD (1980) Small group decision making: the uncertain role of information in reducing uncertainty. Polit Behav 2(2):163–188CrossRefGoogle Scholar
  26. Slevin DP, Boone LW, Rosso EM, Alen RS (1998) CONFIDE: a collective decision-making procedure using confidence estimates of individual judgements. Group Decis Negot 7:179–194CrossRefGoogle Scholar
  27. Sniezek JA (1992) Groups under uncertainty: an examination of confidence in group decision making. Organ Behav Hum Decis Process 52:124–155CrossRefGoogle Scholar
  28. Stanovich KE, West RF (1998) Individual differences in rational thought. J Exp Psychol Gen 127:161–188CrossRefGoogle Scholar
  29. Teleometrics International (2007) NASA moon survival task, Available at: http://www.teleometrics.com/programs/partNumber_1300/info.html
  30. Thagard P (2005) Mind. Introduction to cognitive science, 2nd edn. A Bradford Book, MIT Press, CambridgeGoogle Scholar
  31. Unal R, Keating CB, Chytka TM, Conway BA (2005) Calibration of expert judgments applied to uncertainty assessment. Eng Manag J 12(2):34–43CrossRefGoogle Scholar
  32. Van Swol LM (2009) The effects of confidence and advisor motives on advice utilization. Commun Res 36(6):857–873CrossRefGoogle Scholar
  33. Webber MJ (1977) Pedagogy again: what Is entropy? Ann Assoc Am Geogr 67(2):254–265CrossRefGoogle Scholar
  34. Webster M Jr (2005) Laboratory experiments in social sciences. In: Kempf-Leonard K (coord) Encyclopaedia of social measurement, vol 2. Elsevier Academic Press, OxfordGoogle Scholar
  35. Zamfir C (1980) Schema de evaluare a datelor absolute (SEDA) (The evaluation scheme of absolute data). Viitorul Soc 9(1):70–80Google Scholar
  36. Zamfir C (2005) Incertitudinea — o perspectivă psihosociologică [Uncertainty, a Psycho-sociological Perspective]. Biblioteca de Sociologie, Editura Economică, BucureştiGoogle Scholar
  37. Zarnoth P, Sniezek JA (1997) The social influence of confidence in group decision making. J Exp Soc Psychol 33:345–366CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Institutul de Cercetare a Calităţii VieţiiAcademia RomânăBucharestRomania
  2. 2.Facultatea de Sociologie şi Asistenţă SocialăUniversitatea BucureştiBucharestRomania

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