Profit-Maximizing Cluster Hires

11 Pages Posted: 13 Jul 2014

See all articles by Behzad Golshan

Behzad Golshan

Boston University

Theodoros Lappas

Stevens Institute of Technology - School of Business

Evimaria Terzi

Boston University

Date Written: July 11, 2014

Abstract

Team formation has been long recognized as a natural way to acquire a diverse pool of useful skills, by combining experts with complementary talents. This allows organizations to effectively complete beneficial projects from different domains, while also helping individual experts position themselves and succeed in highly competitive job markets. Here, we assume a collection of projects P, where each project requires a certain set of skills, and yields a different benefit upon completion. We are further presented with a pool of experts X , where each expert has his own skill set and compensation demands. Then, we study the problem of hiring a cluster of experts T ⊆ X , so that the overall compensation (cost) does not exceed a given budget B, and the total benefit of the projects that this team can collectively cover is maximized. We refer to this as the ClusterHire problem. Our work presents a detailed analysis of the computational complexity and hardness of approximation of the problem, as well as heuristic, yet effective, algorithms for solving it in practice. We demonstrate the efficacy of our approaches through experiments on real datasets of experts, and demonstrate their advantage over intuitive baselines. We also explore additional variants of the fundamental problem formulation, in order to account for constraints and considerations that emerge in realistic cluster-hiring scenarios. All variants considered in this paper have immediate applications in the cluster hiring process, as it emerges in the context of different organizational settings.

Keywords: Team Formation, Online Marketplaces

Suggested Citation

Golshan, Behzad and Lappas, Theodoros and Terzi, Evimaria, Profit-Maximizing Cluster Hires (July 11, 2014). Howe School Research Paper No. 2014-34. Available at SSRN: https://ssrn.com/abstract=2465147 or http://dx.doi.org/10.2139/ssrn.2465147

Behzad Golshan

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Theodoros Lappas (Contact Author)

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Evimaria Terzi

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
183
Abstract Views
788
rank
171,124
PlumX Metrics