On the Robustness of Coordination Mechanisms for Investment Decisions Involving ‘Incompetent’ Agents

  • Stephan LeitnerEmail author
  • Doris A. Behrens
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 669)


In this paper we transfer the concept of the competitive hurdle rate (CHR) mechanism introduced by Baldenius et al. (Account Rev 82(4):837–867, 2007) into an agent-based model, and test its robustness with respect to an occurrence of errors in forecasting. We find that our CHR born mechanism is most robust for highly diversified investment alternatives and a limited amount of those projects in need of scarce financial support. For misforecasting both the cash flow time series and the managers’ individual efficiencies of operating investment projects, we find that this result reverses with an increasing extent of being wrong, so that a lower level of project heterogeneity appears to be more advantageous than a highly diversified investment landscape, i.e., if managers are really, really wrong about future economic development, the company fares better (or less worse, to be precise) if the investment alternatives are less dissimilar. This investigation allows to quantify the extent of error, when this comes about. Moreover, we provide policy advice for how an organization could design the framework of the CHR born mechanism so that forecasting errors, which inevitably occur, bring only minimal damage to the company.


Cash Flow Forecast Error Project Diversity Central Office Residual Income 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



A part of Doris A. Behrens’ 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.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty for Business and Economics, Department of Controlling and Strategic ManagementAlpen-Adria Universität KlagenfurtKlagenfurtAustria
  2. 2.Department of Mathematical Methods in Economics, Research Unit for Operations Research and Control SystemsVienna University of TechnologyViennaAustria

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