Representative Decision-Making and the Propensity to Use Round and Sharp Numbers in Preference Specification

  • Gregory E. KerstenEmail author
  • Ewa Roszkowska
  • Tomasz Wachowicz
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 315)


This paper analyzes the agents’ predisposition to produce round numbers during preference elicitation of the pre-negotiation phase. The agents negotiate on behalf of their principals and are asked to use information presented in terms of bar graphs and text to provide their principals’ preferences numerically. In doing that, they tend to use round numbers more often than sharp numbers. Also, more agents use round numbers than sharp numbers, however, the majority of agents use a mix of numbers. The results show that the increased use of round numbers results in greater inaccuracy; the most accurate are agents who use a mix or round and sharp numbers.


Preference reconstruction Direct ratings assignment Ratings accuracy Heuristics Round numbers Sharp numbers 



This research was supported with the grants from Polish National Science Centre (2016/21/B/HS4/01583) and from the Natural Sciences and Engineering Canada.


  1. 1.
    Aloysius, J.A., et al.: User acceptance of multi-criteria decision support systems: the impact of preference elicitation techniques. EJOR 169(1), 273–285 (2006)CrossRefGoogle Scholar
  2. 2.
    Rubin, J.Z., Sander, F.E.: When should we use agents? Direct vs. representative negotiation. Negot. J. 4(4), 395–401 (1988)CrossRefGoogle Scholar
  3. 3.
    Dessein, W.: Authority and communication in organizations. Rev. Econ. Stud. 69(4), 811–838 (2002)CrossRefGoogle Scholar
  4. 4.
    Solet, D.J., et al.: Lost in translation: challenges and opportunities in physician-to-physician communication during patient handoffs. Acad. Med. 80(12), 1094–1099 (2005)CrossRefGoogle Scholar
  5. 5.
    Deci, E.L., Koestner, R., Ryan, R.M.: Extrinsic rewards and intrinsic motivation in education: reconsidered once again. Rev. Educ. Res. 71(1), 1–27 (2001)CrossRefGoogle Scholar
  6. 6.
    Laffont, J.J., Martimort, D.: The Theory of Incentives: The Principal-Agent Model. Princeton University Press, Princeton (2002)Google Scholar
  7. 7.
    Bénabou, R., Tirole, J.: Incentives and prosocial behavior. Am. Econ. Rev. 96(5), 1652–1678 (2006)CrossRefGoogle Scholar
  8. 8.
    Eisenberger, R., Pierce, W.D., Cameron, J.: Effects of reward on intrinsic motivation: negative, neutral, and positive: comment on Deci, Koestner, and Ryan (1999). Psychol. Bull. 125(6), 677–691 (1999)CrossRefGoogle Scholar
  9. 9.
    Chaiken, S., Trope, Y.: Dual-Process Theories in Social Psychology. Guilford Press, New York (1999)Google Scholar
  10. 10.
    Epstein, S.: Cognitive-experiential self-theory of personality. In: Millon, T., Lerner, M.J. (eds.) Handbook of Psychology. Wiley, Hoboken (2003)Google Scholar
  11. 11.
    Simon, H.A., Newell, A.: Heuristic problem solving: the next advance in operations research. Oper. Res. 6(1), 1–10 (1958)CrossRefGoogle Scholar
  12. 12.
    Tversky, A., Kahneman, D.: The framing of decisions and the psychology of choice. Science 211(4481), 453–458 (1981)CrossRefGoogle Scholar
  13. 13.
    Benson, B.: Cognitive bias cheat sheet. Better Humans 2016. Accessed 4 Jan 2017
  14. 14.
    Kaufman, E.L., et al.: The discrimination of visual number. Am. J. Psychol. 62(4), 498–525 (1949)CrossRefGoogle Scholar
  15. 15.
    Dehaene, S.: The Number Sense: How the Mind Creates Mathematics. Oxford University Press, Oxford (2011)Google Scholar
  16. 16.
    Jansen, C.J., Pollmann, M.M.: On round numbers: pragmatic aspects of numerical expressions. J. Quant. Ling. 8(3), 187–201 (2001)CrossRefGoogle Scholar
  17. 17.
    Schindler, R., Yalch, R.: It seems factual, but is it? Effects of using sharp versus round numbers in advertising claims. In: Pechmann, C., Price, L. (eds.) ACR North American Advances, Association for Consumer Research: Duluth, MN, pp. 586–590 (2006)Google Scholar
  18. 18.
    Gilovich, T., Griffin, D., Kahneman, D.: Heuristics and biases: the psychology of intuitive judgment. Cambridge University Press, Cambridge (2002)Google Scholar
  19. 19.
    Schelling, T.C.: The Strategy of Conflict. Harvard University Press, Boston (1980)Google Scholar
  20. 20.
    Alter, A.L., et al.: Overcoming intuition: metacognitive difficulty activates analytic reasoning. J. Exp. Psychol. Gener. 136(4), 569 (2007)CrossRefGoogle Scholar
  21. 21.
    Baird, J.C., Lewis, C., Romer, D.: Relative frequencies of numerical responses in ratio estimation. Attention Percept. Psychophy. 8(5), 358–362 (1970)CrossRefGoogle Scholar
  22. 22.
    Mason, M.F., et al.: Precise offers are potent anchors: conciliatory counteroffers and attributions of knowledge in negotiations. J. Exp. Soc. Psychol. 49(4), 759–763 (2013)CrossRefGoogle Scholar
  23. 23.
    Bizer, G.Y., Schindler, R.M.: Direct evidence of ending-digit drop-off in price information processing. Psychol. Mark. 22(10), 771–783 (2005)CrossRefGoogle Scholar
  24. 24.
    Thomas, M., Morwitz, V.: Penny wise and pound foolish: the left-digit effect in price cognition. J. Consum. Res. 32(1), 54–64 (2005)CrossRefGoogle Scholar
  25. 25.
    Janiszewski, C., Uy, D.: Precision of the anchor influences the amount of adjustment. Psychol. Sci. 19(2), 121–127 (2008)CrossRefGoogle Scholar
  26. 26.
    Pope, D.G., Pope, J.C., Sydnor, J.R.: Focal points and bargaining in housing markets. Games Econ. Behav. 93, 89–107 (2015)CrossRefGoogle Scholar
  27. 27.
    Galinsky, A.D., Mussweiler, T.: First offers as anchors: the role of perspective-taking and negotiator focus. J. Pers. Soc. Psychol. 81(4), 657–669 (2001)CrossRefGoogle Scholar
  28. 28.
    Bazerman, M.H., Neale, M.: Heuristics in negotiation: limitations to dispute resolution effectiveness. In: Bazerman, M.H., Lewicki, R.J. (eds.) Negotiations in Organizations, pp. 51–67. Sage, Beverly Hills (1983)Google Scholar
  29. 29.
    Xie, G.-X., Kronrod, A.: Is the devil in the details? The signaling effect of numerical precision in environmental advertising claims. J. Advertising 41(4), 103–117 (2012)CrossRefGoogle Scholar
  30. 30.
    Roberts, J.M., Brewer, D.D.: Measures and tests of heaping in discrete quantitative distributions. J. Appl. Stat. 28(7), 887–896 (2001)CrossRefGoogle Scholar
  31. 31.
    Kersten, G., Roszkowska, E., Wachowicz, T.: An impact of negotiation profiles on the accuracy of negotiation offer scoring system - experimental study. Multiple Criteria Decis. Making 11, 77–95 (2016)CrossRefGoogle Scholar
  32. 32.
    Roszkowska, E., Wachowicz, T.: Inaccuracy in defining preferences by the electronic negotiation system users. In: International Conference on Group Decision and Negotiation, pp. 131–143. Springer, Heidelberg (2015). Scholar
  33. 33.
    Epstein, S., et al.: Individual differences in intuitive–experiential and analytical–rational thinking styles. J. Pers. Soc. Psychol. 71(2), 390 (1996)CrossRefGoogle Scholar
  34. 34.
    Hutcheson, G., Sofroniou, N.: The Multivariate Social Scientist. Introductory Statistics Using Generalized Linear Models. Sage, London (1999)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Gregory E. Kersten
    • 1
    Email author
  • Ewa Roszkowska
    • 2
  • Tomasz Wachowicz
    • 3
  1. 1.J. Molson School of BusinessConcordia UniversityMontrealCanada
  2. 2.Faculty of Economy and ManagementUniversity of BialystokBialystokPoland
  3. 3.Department of Operations ResearchUniversity of Economics in KatowiceKatowicePoland

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