IDEAS home Printed from https://ideas.repec.org/p/tur/wpapnw/008.html
   My bibliography  Save this paper

Incentive Design and Manager Performances: an ABM Approach

Author

Listed:
  • Concetta Sorropago

    () (University of Roma "Tor vergata", Italy)

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".

Suggested Citation

  • Concetta Sorropago, 2012. "Incentive Design and Manager Performances: an ABM Approach," Working papers 008, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    • Handle: RePEc:tur:wpapnw:008
    as

    Download full text from publisher

    File URL: http://www.bemservizi.unito.it/repec/tur/wpapnw/m8.pdf
    File Function: First version, 2012
    Download Restriction: no

    References listed on IDEAS

    as
    1. George Baker, 2000. "The Use of Performance Measures in Incentive Contracting," American Economic Review, American Economic Association, vol. 90(2), pages 415-420, May.
    2. Canice Prendergast, 1999. "The Provision of Incentives in Firms," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 7-63, March.
    3. Chang, Myong-Hun & Harrington, Joseph Jr., 2006. "Agent-Based Models of Organizations," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 26, pages 1273-1337 Elsevier.
    4. 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 1-1.
    5. 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 9780199243273.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

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

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tur:wpapnw:008. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Simone Pellegrino). General contact details of provider: http://edirc.repec.org/data/dstorit.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.