A fuzzy AHP approach to personnel selection problem

doi:10.1016/j.asoc.2008.09.003

Applied Soft Computing

Volume 9, Issue 2, March 2009, Pages 641-646

https://doi.org/10.1016/j.asoc.2008.09.003 Get rights and content

Abstract

Due to the increasing competition of globalization and fast technological improvements, world markets demand companies to have quality and professional human resources. This can only be achieved by employing potentially adequate personnel. In this paper, we proposed a personnel selection system based on Fuzzy Analytic Hierarchy Process (FAHP). The FAHP is applied to evaluate the best adequate personnel dealing with the rating of both qualitative and quantitative criteria. The result obtained by FAHP is compared with results produced by Yager's weighted goals method. In addition to above-mentioned methods, a practical computer-based decision support system is introduced to provide more information and help manager make better decisions under fuzzy circumstances.

Introduction

In the global market, modern organizations face high levels of competition. In the wake of increasingly competitive world market the future survival of most companies, depends mostly on the dedication of their personnel to companies. Employee or personnel performances such as capability, knowledge, skill, and other abilities play an important role in the success of an organization. The main goal of organizations is to seek more powerful ways of ranking of a set employee or personnel who have been evaluated in terms of different competencies. Great deal of attention in literature was given for the selection of eligible and adequate person among alternative rivals and extensively conducted review can be found in Robertson and Smith [18]. The objective of a selection process depends mainly on assessing the differences among candidates and predicting the future performance. Latter is a challenging task since larger samples are required and other temporal changes may affect employees. Personality factors are generally described as emotional stability, extraversion, openness, agreeableness and conscientiousness Salgado [20]. Jessop [11] determined seven criteria from overview of job description: written communication, oral communication, planning, organizing ability, team player, decisiveness, and working independently. One of the techniques concerning the selection of personnel to fill new positions is to have interviews with related personnel. Robertson and Smith [18] and Cortina et al. [9] present notable ability and availability of interviews to predict the performance of the personnel in the job. The usages of different methods in some European countries are given in Dany and Torchy [10].

As in many decision problems, personnel selection problem is too complicated in real life; humans generally fail to make a good prediction for quantitative problems, whereas comparatively having a good guess in qualitative forecasting. In many situations, individuals mostly prefer to express their feelings with verbal expression. Fuzzy linguistic models permit the translation of verbal expressions into numerical ones. Thereby dealing quantitatively with imprecision in the expression of the importance of each criterion, some multi-criteria methods based on fuzzy relations are used. Fuzzy set theory has been proposed by Miller and Feinzing [16], Karsak [13] and Capaldo and Zollo [4] to rate the personnel selection problem. Fuzzy analytical approach has been applied by Mikhailov [15] to partnership selection problem. Minimally biased weight method has been applied by Jessop [11] in personnel selection. Chen and Cheng [6] proposed a Fuzzy Group Decision Support System (FGDSS) based on metric distance method to solve IS (Information System) in personnel selection problem.

In this type of multi-criteria analysis, AHP is suggested as a tool for implementing a multiple criteria performance scheme. Developed by Saaty [19], the AHP is a simple decision-making tool to cope with complex, unstructured and multi-attributed problems.

The most creative part of decision-making that has an important effect on the outcome is modeling the problem. Identification of the decision hierarchy is the key factor in using AHP. AHP is essential for the formalization of a complex problem using a hierarchical structure and utilizes pair-wise comparisons. AHP has found wide range of applications in industry and other areas. Albayrak and Erensal [1] used AHP, which determines the global priority weights for different management alternatives to improve human performance. A good review is given by Vaidya and Kumar [21] about the applications of AHP. The conventional AHP cannot reflect the human thinking style yet. Therefore, FAHP was developed to solve the hierarchical fuzzy problems. In the FAHP, all calculations are carried out by fuzzy numbers.

In this paper, FAHP method is suggested to solve personnel selection problem using multi-criteria decision-making process. The organization of the paper is as follows: first, the review on fuzzy linguistic and FAHP will be given. Second, fuzzy analytical hierarchy process is constructed and computations are carried out. Then, Yager's weighted method is introduced and applied to the same problem for comparing the results of Yager [23], [22]. In the subsequent section, we introduce and discuss a fuzzy decision support system to help the decision maker. The paper will be ended by the conclusion part.

Section snippets

Fuzzy sets and Fuzzy Numbers

Definition 1 (Fuzzy set)

Let X be a universe of discourse, $\tilde{A}$ is a fuzzy subset of X such that for all x∈X. There is a number $μ_{\tilde{A}} (x) \in [0,1]$ which is assigned to represent the membership of x to $\tilde{A}$ , and $μ_{\tilde{A}} (x)$ is called the membership function of $\tilde{A}$ [24].

Definition 2 (Fuzzy number)

A fuzzy number $\tilde{A}$ is a normal and convex fuzzy subset of X. Here, the ‘convex’ set implies that

\forall x_{1} \in X, x_{2} \in X, \forall α \in [0, 1],

μ_{\tilde{A}} (a x_{1} + (1 - a) x_{2}) \geq \min (μ_{\tilde{A}} (x_{1}), μ_{\tilde{A}} (x_{2})) [24]

Definition 3 (Triangular fuzzy number)

A triangular fuzzy number $\tilde{A}$ can be defined by a triplet (a, b, c). The membership function is defined as

μ_{\tilde{A}} (x)

Illustrative example

As is explained in Section 2.2, we aim at selecting most appropriate person to fulfill the new position. We have three criteria namely general factors pertaining to work, complementary factors pertaining to work and individual factors. The first criterion, the second criterion and the third criterion are sub-divided into six, six, and five criteria, respectively. Table 2, Table 3, Table 4, Table 5 demonstrate the relevant matrix related to first level of hierarchy, criterion A, criterion B, and

Experimental results

In order to demonstrate the usability of Yager's weighted method, two methods are compared with each other under different α-cut levels. For α-cut levels, 0.6, 0.7, 0.8, 0.9, values are used and score values of for each of six alternatives both FAHP and Yager's weighted methods are shown in Table 7. Both methods are programmed and coded in Visual Basic 6.0 programming. The comparison of these two models under different α-cut levels can be considered as a decision support (DS) model since it

Conclusions

In this age of increased competitive markets, the notion of the personnel selection problem has an enormous interest. Decision makers face rising and complex environments today, and also decision makers are often uncertain in assigning the evaluation scores in crisp value. Therefore, in this paper, we tried to design a multi-criteria decision-making model based on fuzzy set theory to select the most adequate person. Unlike other decision methods, the proposed model can adaptively find a

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View full text

A fuzzy AHP approach to personnel selection problem

Abstract

Introduction

Section snippets

Fuzzy sets and Fuzzy Numbers

Illustrative example

Experimental results

Conclusions

Computers in Industry

Omega; the International Journal of Management Science

European Journal of Operation Research

European Journal of Operation Research

European Journal of Operation Research

International Journal of Production Economics

Omega

European Journal of Operation Research

Fuzzy Sets and Systems

Information and Control

European Journal of Operational Research

Using analytic hierarchy process (AHP) to improve human performance: an application of multiple criteria decision making problem

Journal of Intelligent Manufacturing

A fuzzy AHP approach to evaluating machine tool alternatives

Journal of Intelligent Manufacturing