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Incentive Design and Manager Performances: an ABM Approach

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  • Concetta Sorropago

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    (University of Roma "Tor vergata", Italy)

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    Abstract

    We present a simplified model to provide a virtual laboratory to test the effects of the use of different performance evaluation measures to design manager’s incentives in a project-based professional service organization. Our company’s owner has to cope with the scheduling of multiple resource constraint projects in real time (RCMPSP), and with the design of the production manager incentive, whose variable wage is tied to some measures of the performance, which are proxies of the original owner’s goal. We propose an agent based model approach where the agents’ intelligence lies in the choice of the scheduling sequences. A discrete event simulator (DES) executes the projects, allocating in real time, the limited resources available. A Genetic Algorithm, evolving the sequence, randomly generated, uses the DES to simulate the effect and ranks the solutions. In this way, we investigate the incentive alignment problem as a resource allocation problem, comparing the results deriving from their respective "good solutions".

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    File URL: http://eco83.econ.unito.it/RePEc/wp/m8.pdf
    File Function: First version, 2012
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    Bibliographic Info

    Paper provided by Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino in its series Working papers with number 008.

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    Length: 34 pages
    Date of creation: May 2012
    Date of revision:
    Handle: RePEc:tur:wpapnw:008

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    Related research

    Keywords: Complex System Dynamics; Resource constrained multi project scheduling; Incentive Design; Performance Evaluation Measures; Genetic Algorithm;

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    1. Myong-Hun Chang & Joseph E Harrington Jr, 2004. "Agent-Based Models of Organizations," Economics Working Paper Archive 515, The Johns Hopkins University,Department of Economics.
    2. Macho-Stadler, Ines & Perez-Castrillo, J. David, 2001. "An Introduction to the Economics of Information: Incentives and Contracts," OUP Catalogue, Oxford University Press, edition 2, number 9780199243259.
    3. Canice Prendergast, 1999. "The Provision of Incentives in Firms," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 7-63, March.
    4. George Baker, 2000. "The Use of Performance Measures in Incentive Contracting," American Economic Review, American Economic Association, vol. 90(2), pages 415-420, May.
    5. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011 Elsevier.
    6. Andreas Pyka & Claudia Werker, 2009. "The Methodology of Simulation Models: Chances and Risks," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1.
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