A Personnel Selection Model for a Software Development Company based on the ELECTRE III Method and a Variant of NSGA-II.
| Autor | Leyva-Lopez, Juan Carlos |
Introduction
Personnel selection is a significant decision-making problem for organizations, since the effectiveness of choosing the right people for specific tasks improves business performance. This activity can be defined as the process of selecting one or some persons from a set of candidates, considering that the selected individual has the qualities required to perform the assigned work in the best possible way (Zhang & Liu, 2011). In general, personnel selection is to find the appropriate point between a set of specified requirements for the vacant position and the applicants' skills. This problem has been processed in literature through conventional management techniques (Robertson & Smith, 2001) using application forms, initial interviews, employment examinations, and background investigations, among others.
One of the problems of conventional methods for personnel selection is that some of them depend on subjective judgments and exclude derived evaluations from objective analyses. For example, there is continuous feedback between the interviewer and their counterpart during an interview, where judgments of the assessment by the interviewer are modified based on the applicants' characteristics, the interviewer's perceptions, and the interviewing process itself (Eder & Buckley, 1988). Likewise, conventional techniques are predominantly based on statistical analysis, where the solutions are handled as a precise replication of reality.
Using less conventional techniques requiring additional parameters or groups of evaluators (stakeholders) is considered an alternative to combining subjective and objective assessments of candidates in the personnel selection problem. In this sense, Afshari et al. (2010) believe that personnel selection is a complex problem because it operates in function of specific organizational objectives, the availability of resources, and the individual preferences of decision-makers.
Face this problem: he decision-maker should consider a finite set of available applicants. Given this scenario, it is feasible to use the Multicriteria Decision-Making (MCDM) approach to address the personnel selection problem. MCDM considers decision-makers' preferences on the criteria established to evaluate the set of alternatives. Usually, there is no single criterion that captures the performance of each applicant. Besides, through MCDM is possible to reduce the methodological bias, thus obtaining greater accuracy than traditional management methods and a proper way to model the subjectivity of personnel selection processes.
MCDM is an operational research approach that deals with complex decision-making problems with a set of decision alternatives assessed by a coherent family of criteria, where some of these criteria may conflict with each other. MCDM seeks to offer guidelines for decision-makers to resolve multicriteria decision problems. These guidelines can be translated into prescriptions or recommendations regarding the decision that should be made (Figueira et al., 2013). MCDM methods include a wide range of somewhat distinct approaches and can be broadly classified into two categories: discrete MCDM, also known as discrete MADM (Multi-Attribute Decision Making), and continuous Multi-Attribute Decision Making (Multi-Objective Decision Making) methods (Zavadskas & Turskis, 2011). This paper deals with the first type.
MCDM methods have been extensively applied in many real-world multicriteria decision problems in agriculture, environmental management, water management, finance, education, project selection, personnel employing and transportation, and services (Chang, 2014; Govindan & Jepsen, 2016). Recently, multicriteria-based methods have been used to evaluate candidates for a position (Gastelum-Chavira et al., 2017). However, such applications are still limited in quantity and scope. This relatively small number of applications is unusual considering that multicriteria methods can be adapted to economic and social sciences. Hence, this study applies a multicriteria-ranking-based approach in order to assess a set of contenders for a software developer job position in a real business in northwestern Mexico.
With the above in mind, this paper proposes applying an MCDM method to evaluate a set of candidates for a specific position in an organization, that is, to group and rank them considering particular competencies and skills required to perform a defined work in the best possible way.
It is known that human intervention in decision processes intrinsically includes a certain degree of subjectivity; the very evaluation of each candidate with the set of criteria provides subjectivity. The proposed method does not eliminate this subjectivity. However, it includes modeling vagueness as a type of uncertainty through the indifference and preference thresholds. For example, when comparing two candidates in each of the criteria, the decision-maker may consider candidates indifferent in some criteria if the difference between their values does not exceed a specific limit or threshold. These thresholds, however, are also defined subjectively, but allow the comparison to be made more flexible instead of narrowly limiting it. On the other hand, the proposed method tries to minimize inconsistencies related to the integral model of the decision maker's preferences when generating the ranking of candidates.
The remainder of this paper is organized as follows. The section after this introduction contains a description of the personnel selection problem and a literature review from the perspective of MCDM. The section after that includes a summarized version of the ELECTRE III method. In this section we also describe the multi-objective evolutionary algorithm embedded in the software SADGAGE in order to exploit the outranking relation. The analysis of the method in a real multicriteria problem of personnel selection is shown in the subsequent section. Then, we will introduce the results and the discussion around our findings. The last section presents some conclusions and future research lines.
Previous works
Organizations in their human resources processes have widely addressed personnel selection problems using MCDM methods and models as tools that assist in finding the best possible candidate or set of candidates that fulfill the requirements for a position. A large body of research in the literature proposes new applications of MCDM and hybrid methods to better solve these problems. Additionally, the existing literature shows the importance of research in this field and the need to explore more models and methodologies to develop more adequate selection processes for choosing the best candidate.
This section examines recent works on the field published during the 2015-2019 period. Such works present a variety of MCDM methods, such as Analytic Hierarchy Process (AHP) (Saaty, 1980), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Hwang & Yoon, 1981), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) (Mareschal et al., 1984), Elimination Et Choix Traduisant la REalite (ELECTRE) (Roy, 1990), Analytic Network Process (ANP), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Stepwise Weight Assessment Ratio Analysis (SWARA), Multi-multi-objective Optimization on the Basis of Ratio Analysis (MULTIMOORA), Interactive and Multi-criteria Decision-Making (TODIM), Additive Ratio Assessment (ARAS-G), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), Eighted Average (OWA), COmbinative Distance-Based ASsessment (CODAS), and the Decision Making Trial and Evaluation Laboratory (DEMATEL).
As examples, Kusumawardani and Agintiara (2015) used AHP with TOPSIS for the manager selection problem in a telecommunications company. Sang et al. (2015) presented some experiments to analyze the impact of using fuzzy TOPSIS in the personnel selection application at a software company. Besides, Liu et al. (2015) introduced a 2-tuple linguistic VIKOR method and its application to a nurse recruitment problem in a tertiary care hospital as a group decision approach. Moreover, Alguliyev et al. (2015) proposed a fuzzy VIKOR method to solve a real decision-making problem aimed at ranking a set of candidates for the selection of the best option to fill a position at an innovation technology center. For their part, Karabasevic et al. (2015) introduced a hybrid MCDM method based on SWARA and MULTIMOORA methods to select the best candidate for an engineering position in the mining industry.
In the same line, Bilgehan-Erdem (2016) proposed Fuzzy AHP as an approach for personnel selection problems in IT companies, presenting a case study for the selection of a developer for a university development department. Yu et al. (2017) extended the TODIM method for multicriteria group decision making (MCGDM) problems with unbalanced HFLTSs, illustrating its applicability in the selection problem of a sales manager for a company in the manufacturing industry. In the work by Urosevic et al. (2017), the SWARA and grey ARAS-G methods are proposed to resolve the personnel selection problem within the tourism industry, offering a hypothetical example to evaluate and select a sales manager. Stanujkic et al. (2017) tackled a problematic choice by integrating the Adapted Weighted Sum and SWARA methods in a personnel selection case study of three promoters for a marketing company.
Dahooie et al. (2018) introduced a multicriteria framework for IT personnel selection based on five competency class attributes. This framework is based on the ARAS-G method to weight the expert evaluation of criteria and the SWARA method to rank the candidates. Samanlioglu et al. (2018) presented an integrated approach based on the Fuzzy AHP and TOPSIS methods to select the best candidate for an IT position at a dairy company. Dung et al. (2018) used TOPSIS along...
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