Optimal task assignments with loss-averse agents.
This paper studies optimal task assignments in a setting where agents are expectation-based loss averse according to Köszegi and Rabin (2006, 2007) and are compensated according to an aggregated performance measure in which tasks are technologically independent. We show that the optimal task assignm...
| Publicado en: | European Economic Review Vol. 105; pp. 1 - 27 |
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| Autor principal: | |
| Formato: | Artículo |
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Elsevier B.V.
Jun2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=129589211&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 129589211 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00142921 EER jtl: European Economic Review issn: 00142921 maglogo: N pubinfo: dt: Jun2018 vid: 105 pid: 1004 pub: Elsevier B.V. artinfo: ui: 129589211 10.1016/j.euroecorev.2018.03.006 ppf: 1 ppct: 26 formats: tig: atl: Optimal task assignments with loss-averse agents. aug: au: Balmaceda, Felipe affil: Economics Department, Diego Portales University, Avda. Santa Clara 797, Santiago 8580000, Chile su: Task performance Loss aversion Computer multitasking Conjoint analysis Economic specialization Direct costing sug: subj: Task performance Loss aversion Computer multitasking Conjoint analysis Economic specialization Direct costing keyword: Complementarities D03 D21 D86 D90 Expectation-based loss aversion Implementation J24 J33 J41 Multitasking Specialization Complementarities D03 D21 D86 D90 Expectation-based loss aversion Implementation J24 J33 J41 Multitasking Specialization ab: This paper studies optimal task assignments in a setting where agents are expectation-based loss averse according to Köszegi and Rabin (2006, 2007) and are compensated according to an aggregated performance measure in which tasks are technologically independent. We show that the optimal task assignment is determined by a trade-off between paying lower compensation costs and restricting the set of implementable effort profiles under multitasking. We show that loss aversion combined with how much the marginal cost of effort in one task increases with the effort chosen in other tasks determines when multitasking saves on compensation costs, but results in an implementation problem. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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