nach oben

Group Decision and Negotiation

Erschienen in:

19.03.2015

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

verfasst von: Alexandra Gheondea-Eladi

Erschienen in: Group Decision and Negotiation | Ausgabe 1/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

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.

Vorheriger Artikel Generalized Hybrid Aggregation Operators Based on the 2-Dimension Uncertain Linguistic Information for Multiple Attribute Group Decision Making

Nächster Artikel Conflicting Bifuzzy Multi-attribute Group Decision Making Model with Application to Flood Control Project

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

We say that a function of time oscillates if, for a significant period of time, it increases and decreases consecutively for a significant number of times.

The constant solution of a linear differential equation with constant coefficients and constant forcing function is called the equilibrium solution; given another solution, we say that it has an evolution to equilibrium if, as time goes, it becomes closer and closer to the equilibrium solution (asymptotically converges to the equilibrium value) (Medio and Lines 2001: 25).

The state space (phase space, configuration space) is the space of the dependent variables (the variables that specify the state of the system); in the context of the proposed model, it is \(\mathbb {R}\) (the real line) (Medio and Lines 2001:11).

In the context described at the beginning of Sect. 2 regarding the view of individual characteristics as comprising of both social and individual characteristics.

We thank Cătălin Zamfir for bringing this issue to our attention.

Beck and Katz (2007) show that least-squares approximations for time series in cross-section data are appropriate only if the errors are spherical. This means that the variance of the distribution of variances of residuals is relatively small (\(VVR\,=\,1.649589\)) and that the correlation matrix of the residuals is diagonal (has close to \(0\) correlations outside of the diagonal). The results of this analysis showed that the use of the ordinary least-squares approximation method employed is justified and appropriate.

Beck N, Katz J (1995) What to do (and not to do) with time-series cross-section data. Am Polit Sci Rev 89(3):634–647CrossRef

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

Chadwick B, Bahr HH, Albrecht SL (1984) Social science research methods. Prentice-Hall, New Jersey

Cromley RG (1982) The Von Thünen model and environmental uncertainty. Ann Assoc Am Geogr 72(3):404–410CrossRef

Dean A, Voss D (1999) Design and analysis of experiments. Springer, New York

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):883–903

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

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):305–326CrossRef

Hirokawa RY, Poole MS (1996) Communication and group decision making. Sage, Thousand OaksCrossRef

Hirsch MW, Smale S (1974) Differential equations, dynamical systems, and linear algebra, Pure and Applied Mathematics, vol 60. Academic Press, New York-London, Cambridge

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

Kahn BE, Sarin RK (1988) Modeling ambiguity in decisions under uncertainty. J Consum Res 15:265–272CrossRef

Kobus DA, Proctor S, Holste S (2001) Effects of experience and uncertainty during dynamic decision making. Int J Ind Ergon 28:275–290CrossRef

Laughlin PR (2011) Social choice theory, social decision scheme theory, and group decision-making. Group Process Intergroup Relat 14(1):63–79CrossRef

Mann P (2010) Introductory statistics, 6th edn. Wiley, London

Medio A, Lines M (2001) Nonlinear dynamics: a primer. Cambridge University Press, CambridgeCrossRef

Moscovici S, Doise W (1994) Conflict and consensus. Sage, London

Niederman F, Bryson J (1998) Influence of computer-based meeting support on process and outcomes for divisional coordinating group 7:293–325

Nøretranders T (2009/1991), Iluzia utilizatorului. Despre limitele conştiinţei [The user illusion. Cutting consciousness down to size], Publica, Bucureşti

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 York

Payne JW, Bettman JR, Johnson EJ (1993) The adaptive decision maker. Cambridge University Press, CambridgeCrossRef

Pedler E (2001) Sociologia comunicării [Sociology of Communication]. Syracuza Collection, Cartea Românească, Bucureşti

Prutianu T (2004) Antrenamentul abilităilor de comunicare [Trainning the communication abilities. Polirom, Bucureşti

Punchochar JM, Fox PW (2004) Confidence in individual and group decision making: when “Two Heads” are worse than one. J Educ Psychol 96(3):582–591CrossRef

Robertson RD (1980) Small group decision making: the uncertain role of information in reducing uncertainty. Polit Behav 2(2):163–188CrossRef

Slevin DP, Boone LW, Rosso EM, Alen RS (1998) CONFIDE: a collective decision-making procedure using confidence estimates of individual judgements. Group Decis Negot 7:179–194CrossRef

Sniezek JA (1992) Groups under uncertainty: an examination of confidence in group decision making. Organ Behav Hum Decis Process 52:124–155CrossRef

Stanovich KE, West RF (1998) Individual differences in rational thought. J Exp Psychol Gen 127:161–188CrossRef

Teleometrics International (2007) NASA moon survival task, Available at: http://www.teleometrics.com/programs/partNumber_1300/info.html

Thagard P (2005) Mind. Introduction to cognitive science, 2nd edn. A Bradford Book, MIT Press, Cambridge

Unal R, Keating CB, Chytka TM, Conway BA (2005) Calibration of expert judgments applied to uncertainty assessment. Eng Manag J 12(2):34–43CrossRef

Van Swol LM (2009) The effects of confidence and advisor motives on advice utilization. Commun Res 36(6):857–873CrossRef

Webber MJ (1977) Pedagogy again: what Is entropy? Ann Assoc Am Geogr 67(2):254–265CrossRef

Webster M Jr (2005) Laboratory experiments in social sciences. In: Kempf-Leonard K (coord) Encyclopaedia of social measurement, vol 2. Elsevier Academic Press, Oxford

Zamfir C (1980) Schema de evaluare a datelor absolute (SEDA) (The evaluation scheme of absolute data). Viitorul Soc 9(1):70–80

Zamfir C (2005) Incertitudinea — o perspectivă psihosociologică [Uncertainty, a Psycho-sociological Perspective]. Biblioteca de Sociologie, Editura Economică, Bucureşti

Zarnoth P, Sniezek JA (1997) The social influence of confidence in group decision making. J Exp Soc Psychol 33:345–366CrossRef

Titel: The Evolution of Certainty in a Small Decision-Making Group by Consensus
verfasst von: Alexandra Gheondea-Eladi
Publikationsdatum: 19.03.2015
Verlag: Springer Netherlands
Erschienen in: Group Decision and Negotiation / Ausgabe 1/2016
Print ISSN: 0926-2644
Elektronische ISSN: 1572-9907
DOI: https://doi.org/10.1007/s10726-015-9436-8

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2016

(Un)expected Bidder Behavior in Spectrum Auctions: About Inconsistent Bidding and Its Impact on Efficiency in the Combinatorial Clock Auction

An Acceptable Consistency-Based Framework for Group Decision Making with Intuitionistic Preference Relations

Generalized Hybrid Aggregation Operators Based on the 2-Dimension Uncertain Linguistic Information for Multiple Attribute Group Decision Making

Application of Fuzzy Risk Analysis for Selecting Critical Processes in Implementation of SPC with a Case Study

Client Perceptions of Reported Outcomes of Group Model Building in the New Zealand Public Sector

Conflicting Bifuzzy Multi-attribute Group Decision Making Model with Application to Flood Control Project

Premium Partner