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dc.contributor.authorCunha, Raissa Damasceno-
dc.contributor.authorSerrano, André Luiz Marques-
dc.contributor.authorFranco, Vithor Rosa-
dc.contributor.authorGuarnieri, Patricia-
dc.date.accessioned2019-01-24T12:40:10Z-
dc.date.available2019-01-24T12:40:10Z-
dc.date.issued2018-
dc.identifier.citationCUNHA, Raissa Damasceno et al. Staff sizing as a mechanism of efficiency: an application of a non-parametric method. Cogent Business & Management, n. 5, art. 1463835. DOI: https://doi.org/10.1080/23311975.2018.1463835. Disponível em: https://www.cogentoa.com/article/10.1080/23311975.2018.1463835. Acesso em: 24 jan. 2019.pt_BR
dc.identifier.urihttp://repositorio.unb.br/handle/10482/33803-
dc.language.isoInglêspt_BR
dc.publisherCogent oapt_BR
dc.rightsAcesso Abertopt_BR
dc.titleStaff sizing as a mechanism of efficiency : an application of a non-parametric methodpt_BR
dc.typeArtigopt_BR
dc.subject.keywordPlanejamento de mão-de-obrapt_BR
dc.subject.keywordAnálise de envoltória de dadospt_BR
dc.subject.keywordPequenas e médias empresaspt_BR
dc.rights.license© 2018 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.pt_BR
dc.description.abstract1The concept of staff sizing aims to estimate or determine the ideal or optimal number of people needed to perform some organizational activities, which can be considered as a trend. So, models for staff sizing constitute a fundamental part of accurately identifying staff allocation. The objective of this paper is to propose a framework for decision-making based on Data Envelopment Analysis–DEA, to estimate the staff sizing in a Brazilian entity responsible for promoting and supporting the competitiveness and sustainable development of micro and small enterprises. Data collection was carried out in the headquarters of the entity, located in Brasilia. Firstly, interviews were carried with managers in order to assess qualitatively the needs of staff for each service unit. Secondly, the documental analysis of reports from 21 units was analyzed quantitatively in order to determine their efficiency in terms of staff sizing. The results found through DEA show that only three service units can be considered efficient in terms of staff sizing. Thus, there is a need to reduce the number of workers in most of the organization. In this context, the contributions for the entity lie in the discussion on the creation of quantitative indicators and the adoption of an efficiency analysis, which can be used to better estimate or determine the optimal quantity of staff. This paper innovates by proposing a quantitative and systematized approach to estimate the staff sizing, which is the DEA.pt_BR
dc.description.unidadeFaculdade de Economia, Administração, Contabilidade e Gestão de Políticas Públicas (FACE)pt_BR
dc.description.unidadeDepartamento de Administração (FACE ADM)pt_BR
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