Abstract
This paper analyzes how managers suffering from decision-making biases in interrelated decision processes affect the performance of an overall business organization. To perform the analysis, we utilize an NK-type agent-based simulation model, in which decision-making is represented by adaptive walks on performance landscapes. We find that organizational performance holds up well, if the decision problem breaks into disjointed sub-problems. If decisions are, however, highly cross-related between departments, the overall organization’s performance degrades, while both negatively phrasing information and relying more heavily on recently derived information account for an improvement. The effect of positively phrasing information that is relevant for decision-making works towards the same direction, but much more reluctantly. These results cautiously raise doubt about the claim that decision-making should always be as rational as possible.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
The model contains a fitness landscape representing the objective, the overall organizational performance, in which agents seek to incrementally improve their payoffs. This behavior corresponds to moving step by step from ‘fitness valleys’ to ‘fitness peaks’.
- 4.
- 5.
Note that the central office does not intervene in decentralized decision-making. It exercises influence only via providing incentives (by controlling γ j). Moreover, the central office is obliged to note both departments’ configurations ranked first, and, at the end of period \(t\), to observe the performance of the combined configuration d \(_{t}^{{\ast}}\) = [d \(_{t}^{1{\ast}}\) … d \(_{t}^{N{\ast}}\)].
- 6.
This finding is based on the fact that a higher degree of interrelation causes performances landscapes to be more rugged, which, in turn, makes it more difficult to find the global peak. A result resembling ours with respect to interrelatedness is provided by Stark and Behrens [22, 23], who show within the context of an evolutionary game being played on a ring network that a lower degree of information and interaction accessible on the individual level (and thereby ‘reducing the size’ of the problem to be solved by the individual), respectively, can improve the performance of the overall system.
- 7.
Reading Table 2, it is plausible to assume that the non-significant effect of positive framing would turn into a significantly positive effect once the corresponding parameter range was extended, i.e., for β W j > 0. 2.
References
Berlinger S, Wall F (2013) Effects of combined human decision-making biases on organizational performance. In: Amblard F, Giardini F (eds) Multi-agent-based simulation XII. Volume to appear of LNCS. Springer, Berlin/Heidelberg
Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci USA 99(Suppl 3):7280–7287
Bredenkamp J, Wippich W (1977) Lern- und Gedächtnispsychologie I. Kohlhammer, Stuttgart
Chang MH, Harrington JE (2006) Agent-based models of organizations. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics. Agent-based computational economics, vol 2. North Holland, Amsterdam, pp 1273–1337
Davis JP, Eisenhardt KM, Bingham CB (2007) Developing theory through simulation methods. Acad Manag Rev 32(2):480–499
Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–292
Kauffman SA (1993) The origins of order. Self-organization and selection in evolution. Oxford University Press, New York
Kauffman SA (1995) At home in the universe. The search of laws for self-organization and complexity. Oxford University Press, New York
Kauffman SA, Levin S (1987) Towards a general theory of adaptive walks on rugged landscapes. J Theor Biol 128(1):11–45
Kauffman SA, Weinberger ED (1989) The NK model of rugged fitness landscapes and its application to maturation of the immune response. J Theor Biol 141:211–245
Leitner S, Behrens DA (2013) On the fault (in)tolerance of coordination mechanisms for distributed investment decisions: results of an agent-based simulation. Working paper, Alpen-Adria Universität Klagenfurt (in submission)
Leitner S, Wall F (2011) Effectivity of multi criteria decision-making in organisations: results of an agent-based simulation. In: Osinga S, Hofstede GJ, Verwaart T (eds) Emergent results of artificial economics. Volume 652 of LNEMS. Springer, Berlin/Heidelberg, pp 79–90
Leitner S, Wall F (2011) Unexpected positive effects of complexity on performance in multiple criteria setups. In: Hu B, Morasch K, Pickl S, Siegle M (eds) Operations research proceedings 2010 Munich. Springer, Berlin/Heidelberg, pp 577–582
Leitner S, Wall F (2013) Multi objective decision-making policies and coordination mechanisms in hierarchical organizations: results of an agent-based simulation. Working paper, Alpen-Adria Universität Klagenfurt (in submission)
Moss S (2001) Editorial introduction: Messy systems—the target for multi agent based simulation. In: Moss S, Davidsson P (eds) Multi-agent-based simulation. Volume 1979 of LNCS. Springer, Berlin/Heidelberg, pp 1–14
Porter ME (1996) What is strategy? Harv Bus Rev 74(6):61–78
Rivkin JW, Siggelkow N (2003) Balancing search and stability: interdependencies among elements of organizational design. Manag Sci 49(3):290–311
Rivkin JW, Siggelkow N (2007) Patterned interactions in complex systems: implications for exploration. Manag Sci 53(7):1068–1085
Siggelkow N, Levinthal DA (2003) Temporarily divide to conquer: centralized, decentralized, and reintegrated organizational approaches to exploration and adaptation. Organ Sci 14(6):650–669
Siggelkow N, Rivkin JW (2005) Speed and search: designing organizations for turbulence and complexity. Organ Sci 16(2):101–122
Sprinkle GB (2003) Perspectives on experimental research in managerial accounting. Account Organ Soc 28(2–3):287–318
Stark O, Behrens DA (2010) An evolutionary edge of knowing less (or: on the curse of global information). J Evol Econ 20(1):77–94
Stark O, Behrens DA (2011) In search of an evolutionary edge: trading with a few, more, or many. J Evol Econ 21(5):721–736
Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Sci New Ser 185(4157):1124–1131
Tversky A, Kahneman D (1981) The framing of decisions and the psychology of choice. Sci New Ser 211(4481):453–458
Tversky A, Kahneman D (1986) Rational choice and the framing of decisions. J Bus 59(4):251–278
Wall F (2010) The (beneficial) role of informational imperfections in enhancing organisational performance. In: LiCalzi M, Milone L, Pellizzari P (eds) Progress in artificial economics. Computational and agent-based models. Volume 645 of LNEMS. Springer, Berlin/Heidelberg, pp 115–126
Weinberger E (1991) Local properties of Kauffman’s N-K model: a tunably rugged energy landscape. Phys Rev A 44(10):6399–6413
Acknowledgements
This work was carried out within the framework of the SOSIE project and was supported by Lakeside Labs GmbH. It was funded by the European Regional Development Fund (ERDF) and the Carinthian Economic Promotion Fund (KWF) under grant no. 20214/23793/35529.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Behrens, D.A., Berlinger, S., Wall, F. (2014). Phrasing and Timing Information Dissemination in Organizations: Results of an Agent-Based Simulation. In: Leitner, S., Wall, F. (eds) Artificial Economics and Self Organization. Lecture Notes in Economics and Mathematical Systems, vol 669. Springer, Cham. https://doi.org/10.1007/978-3-319-00912-4_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-00912-4_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00911-7
Online ISBN: 978-3-319-00912-4
eBook Packages: Business and EconomicsEconomics and Finance (R0)