IAC in Vienna 2019, Vienna, Austria, 29 - 30 November 2019, pp.175-181
Personnel selection, which
is of great importance in terms of human resources management, is the process
of selecting individuals who are suitable for the qualifications required to
perform a defined job in the best way. The growing importance attached to
personnel selection has paved the way for analytical decision making
approaches. This work introduces a common- weight data
envelopment analysis (DEA) based multi-criteria decision making (MCDM) aid for evaluating
the candidates throughout the
recruitment process of a bank. The developed two-phase
approach is based on minimizing the sum of deviations from efficiency. The
proposed methodology guarantees to identify the best performing candidate with
respect to the defined attributes via solving a mixed integer linear programming
model in addition to a single linear program. Comparative analyses demonstrate improved discriminatory characteristics
and computational efficiency of the proposed approach.