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Optimal team composition for tool‐based problem solving
dc.contributor.authorBendor, Jonathan
dc.contributor.authorPage, Scott E.
dc.date.accessioned2019-11-12T16:24:05Z
dc.date.availableWITHHELD_13_MONTHS
dc.date.available2019-11-12T16:24:05Z
dc.date.issued2019-11
dc.identifier.citationBendor, Jonathan; Page, Scott E. (2019). "Optimal team composition for tool‐based problem solving." Journal of Economics & Management Strategy 28(4): 734-764.
dc.identifier.issn1058-6407
dc.identifier.issn1530-9134
dc.identifier.urihttps://hdl.handle.net/2027.42/152035
dc.description.abstractIn this paper, we construct a framework for modeling teams of agents who apply techniques or procedures (tools) to solve problems. In our framework, tools differ in their likelihood of solving the problem at hand; agents, who may be of different types, vary in their skill at using tools. We establish baseline hiring rules when a manager can dictate tool choice and then derive results for strategic tool choice by team members. We highlight three main findings: First, that cognitively diverse teams are more likely to solve problems in both settings. Second, that teams consisting of types that master diverse tools have an indirect strategic advantage because tool diversity facilitates coordination. Third, that strategic tool choice creates counterintuitive optimal hiring practices. For example, optimal teams may exclude the highest ability types and can include dominated types. In addition, optimal groups need not increase setwise. Our framework extends to cover teamwork on decomposable problems, to cases where individuals apply multiple tools, and to teams facing a flow or set of problems.
dc.publisherBasic Books
dc.publisherWiley Periodicals, Inc.
dc.titleOptimal team composition for tool‐based problem solving
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelEconomics
dc.subject.hlbsecondlevelManagement
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152035/1/jems12295.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152035/2/jems12295_am.pdf
dc.identifier.doi10.1111/jems.12295
dc.identifier.sourceJournal of Economics & Management Strategy
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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