How to pick your staff? Using data envelopment analysis
Abstract
Purpose
This purpose of this paper is to present a tool for facilitating personnel selection when multiple heterogeneous human resource managers use multiple criteria. Two problems result from such a situation. First, when multiple criteria are applied, it is unusual for one candidate to dominate the other candidates in all areas, which requires assigning weights to the different criteria to be able to rank the candidates. Second, in a heterogeneous selection committee, finding weights that accurately reflect the individual preferences of all members is difficult.
Design/methodology/approach
To deal with the multidimensional setting of selecting personnel, this paper introduces data envelopment analysis with assurance region (DEA-AR) to determine individually optimal weights for each applicant.
Findings
DEA-AR leads to a score for each applicant that can serve as a signal for productivity and, thus, for evaluating the candidate. Based on linear programming, DEA-AR not only aggregates multiple dimensions into a single score but also incorporates managers’ preferences. In addition, the procedure is transparent and fair. It seems to be highly appropriate for selecting personnel. Based on a simulated dataset of applicants, the use of DEA-AR for selecting personnel is illustrated and discussed.
Originality/value
DEA-AR provides a tool for supporting personnel selection or pre-selection. This model is based on a mechanical procedure and considers managers’ ideas about weights.
Keywords
Citation
Warning, S. (2014), "How to pick your staff? Using data envelopment analysis", Management Research Review, Vol. 37 No. 9, pp. 815-832. https://doi.org/10.1108/MRR-05-2013-0104
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited