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Murat Bayiz is a Professor of Clinical Data Sciences and Operations at Marshall School of Business. He has more than two decades of combined management consulting and academic experience and specializes in operations strategy.Murat teaches core and elective at Marshall School’s undergraduate, MS in GSCM, and MBA programs. In recent years he received six Golden Apple awards for teaching excellence and the Evan Thompson award for teaching and learning innovation.Prior to joining USC, Murat was a management consultant at PRTM Management Consultants (later acquired by PwC) and Kiran Analytics and consulted with high tech companies on supply chain strategy projects.
RESEARCH + PUBLICATIONS
We study the problem of the manager of a project consisting of multiple sub-projects
or tasks which are outsourced to different subcontractors. The project manager earns
more revenue if the project is completed faster, but cannot observe subcontractors’ effort,
only the stochastic duration of their tasks. We outline how to determine the optimal
linear contracts for general networks with normally distributed activity durations using
an approximation from Clark (1961). We then derive the optimal linear contracts for the
case with n multiple tasks in series or two tasks in parallel. We discuss when incentive
contracts lead to bigger performance improvements compared to the fixed-price contracts often encountered in practice. We characterize how the incentive contracts vary with the subcontractors’ risk aversion and cost of effort, the marginal effect of subcontractor effort, and the variability of task durations. This dependence is sometimes counter-intuitive. For
parallel tasks, if the first agent’s task is on the critical path and his variability increases,
the project manager should induce the first agent to work less hard and the second agent to
work harder. Our numerical analysis of more complex networks suggests that the structure
of project networks affects the optimal contracts and that the value of incentive contracts and the value of information are higher in projects with a dominant critical path than in
projects with many parallel critical paths.