Predicting Response of Risk-Seeking Systems during Project Negotiations in a System of Systems
Abstract
During project negotiations, typically, the awarding agency seeks bids from multiple parties. Examples of this setting include firms that are no longer willing to produce parts in-house or an airport seeking contracts for renovation. Risk-seeking parties are those that agree to work with lower budgets and under shorter deadlines, whereas risk-averse parties exhibit the opposite behavior. This setting can be found in the context of system of systems (SoS), where the SoS coordinator (the firm) has access to behavior characteristics of individual systems (parties) and their current workload from past interactions. The problem we study is for the SoS coordinator to predict the response of the systems in terms of budgets, deadlines, and performance targets, in advance of obtaining the actual response. This prediction can help the SoS negotiate the best deal. We present a quantitative model that predicts this response. Our model employs Markov chains to capture dynamics of the project, which would result when a bid is won, to quantify the response. Furthermore, our model accounts for the risk-taking tendencies and agility of the firm. We also analyze mathematical properties and provide numerical results to illustrate how our model can be used in a negotiation process.
Recommended Citation
A. Gosavi et al., "Predicting Response of Risk-Seeking Systems during Project Negotiations in a System of Systems," IEEE Systems Journal, vol. 11, no. 3, pp. 1557 - 1566, Institute of Electrical and Electronics Engineers (IEEE), Sep 2017.
The definitive version is available at https://doi.org/10.1109/JSYST.2015.2495198
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Budgets; entrepreneurial risk (ER); Markov chains; project negotiations; system of systems (SoS)
International Standard Serial Number (ISSN)
1932-8184
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Sep 2017
Comments
This work was supported in part by the U.S. Department of Defense through the Systems Engineering Research Center (SERC) under Contract H98230-08-D-0171. SERC is a federally funded University-Affiliated Research Center managed by Stevens Institute of Technology.