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The Impact of Contractor Behavior on the Client's Payment-Scheduling Problem

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  • Joseph G. Szmerekovsky

    (Department of Management, Marketing and Finance, College of Business Administration, North Dakota State University, Fargo, North Dakota 58105)

Abstract

Recent approaches to modeling the client's payment-scheduling problem allow the client to control both the timing of payments and the completion times of activities. In practice, the activity schedule is typically determined by the contractor rather than the client. This paper addresses this drawback by considering a model in which the client selects the payment activities and the contractor selects the activity schedule, each to maximize his own net present value (NPV). In addition, the contractor has the option to reject the project if it does not provide a minimum NPV. The new model is shown to be NP-hard in the strong sense and a branch-and-bound procedure is provided for its solution. Results are obtained for the new model that contradict those of the older models. The benefits to the client are no longer increasing with retention and no longer decreasing with the number of payments. Furthermore, it is no longer ideal for the client to focus payments at the beginning and end of the project. Empirical evidence based on a randomly generated data set suggests that the market for the contractor's services, the timing of benefits received by the client, and the project duration drive these new results.

Suggested Citation

  • Joseph G. Szmerekovsky, 2005. "The Impact of Contractor Behavior on the Client's Payment-Scheduling Problem," Management Science, INFORMS, vol. 51(4), pages 629-640, April.
    • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:4:p:629-640
    DOI: 10.1287/mnsc.1040.0319
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    References listed on IDEAS

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    1. A. H. Russell, 1970. "Cash Flows in Networks," Management Science, INFORMS, vol. 16(5), pages 357-373, January.
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    Cited by:

    1. Zhang, Jingwen & Elmaghraby, Salah E., 2014. "The relevance of the “alphorn of uncertainty” to the financial management of projects under uncertainty," European Journal of Operational Research, Elsevier, vol. 238(1), pages 65-76.
    2. Zhengwen He & Nengmin Wang & Pengxiang Li, 2014. "Simulated annealing for financing cost distribution based project payment scheduling from a joint perspective," Annals of Operations Research, Springer, vol. 213(1), pages 203-220, February.
    3. Creemers, Stefan, 2018. "Moments and distribution of the net present value of a serial project," European Journal of Operational Research, Elsevier, vol. 267(3), pages 835-848.
    4. Cyril Briand & Sandra Ulrich Ngueveu & Přemysl Šůcha, 2017. "Finding an optimal Nash equilibrium to the multi-agent project scheduling problem," Journal of Scheduling, Springer, vol. 20(5), pages 475-491, October.
    5. Sobel, Matthew J. & Szmerekovsky, Joseph G. & Tilson, Vera, 2009. "Scheduling projects with stochastic activity duration to maximize expected net present value," European Journal of Operational Research, Elsevier, vol. 198(3), pages 697-705, November.
    6. Nursel Kavlak & Gündüz Ulusoy & Funda Sivrikaya Şerifoğlu & Ş. İlker Birbil, 2009. "Client‐contractor bargaining on net present value in project scheduling with limited resources," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(2), pages 93-112, March.

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