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Título: Staff sizing as a mechanism of efficiency : an application of a non-parametric method
Autor(es): Cunha, Raissa Damasceno
Serrano, André Luiz Marques
Franco, Vithor Rosa
Santos, Patricia Guarnieri dos
Assunto: Planejamento de mão-de-obra
Análise de envoltória de dados
Pequenas e médias empresas
Data de publicação: 2018
Editora: Cogent oa
Referência: CUNHA, 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.
Abstract: The 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.
Licença: © 2018 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
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