Multicriteria job evaluation for large organizations

Spyridakos, Athanasios; Siskos, Yannis; Yannacopoulos, Denis; Skouris, A.

doi:10.1016/s0377-2217(00)00039-4

Cited by 46 publications

(30 citation statements)

References 6 publications

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“…Fuzzy set theory has been proposed (Miller and Feinzig, 1993;Karsak, 2001;Capaldo and Zollo, 2001) as have the applications of linear weighted sums familiar in multicriteria analyses (Bohanec, Urh and Rajkovič,1992;Gardiner and Armstrong-Wright, 2000;Spyridakos et al, 2001). Timmermans and Vlek (1992; explore how the use of formal methods may help in overcoming bias and information overload and conclude that using a weighted sum for aggregation is of use for some problems but that it is unnecessary for small problems and fails to be of help in large complex problems.…”

Section: Formal Methodsmentioning

confidence: 99%

Minimally biased weight determination in personnel selection

Jessop

2004

European Journal of Operational Research

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThe derivation of weights from preference statements is subject to difficulties, some of which are due to the unreliability of the judgement of the decision maker. To overcome this Jaynes' principle of maximum entropy has been invoked and may be applied either to weights or to the linear weighted scores of the candidates in a selection problem. When candidates are relatively few the two strategies give different styles of interaction. These are discussed and illustrated by application to a problem of personnel selection.

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Section: Formal Methodsmentioning

confidence: 99%

Minimally biased weight determination in personnel selection

Jessop

2004

European Journal of Operational Research

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“…The firm receives numerous applications from very different candidates. Let the relevant outputs[9] for this position consider the candidate's specific job and general performance as well as qualitative and quantitative measures (Spyridakos et al, 2001;Manoharan et al, 2009). In particular, the outputs are the number of successful projects, the total financial volume of all projects, the total score on a foreign language test and the rating from an interview.…”

Section: Data and Measurementmentioning

confidence: 99%

“…However, some studies propose MRR 37,9 formal aggregation methods for selecting personnel. These include linear weighted sums (Spyridakos et al, 2001), multi-criteria modeling (Jessop, 2004;Roth and Bobko, 1997) and fuzzy set theory (Capaldo and Zollo, 2001;Liang and Wang, 1994). Formal aggregation methods are becoming popular, as they help reduce the effect of interviewer subjectivity, technical bias and socially undesirable biases such as gender or racial bias (Jessop, 2004).…”

Section: Introductionmentioning

confidence: 99%

How to pick your staff? Using data envelopment analysis

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2014

Management Research Review

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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.

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“…Personnel selection factors taken into consideration were classified in three groups, each one of which being professional skills, managerial skills, and personnel characteristics. Multi-criteria analyses are other personnel selection methods reported in literature (Bohanec et al1992;Timmermans andVlek 1992, 1996; Gardiner and Armstrong-Wright 2000; Spyridakos et al 2001;Jessop 2004). These methods can be effectively employed while evaluating a multitude of factors together in the solution of especially large and complicated problems (Dagdeviren and Yuksel, 2007).…”

Section: Literature Reviewmentioning

confidence: 99%