Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology

Dahooie, Jalil Heidary; Abadi, Elham Beheshti Jazan; Vanaki, Amir Salar; Firoozfar, Hamid Reza

doi:10.1002/hfm.20713

Cited by 98 publications

(46 citation statements)

References 74 publications

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“…However, the SWARA method, like DEMATEL, does not have the ability to determine the consistency degree of the comparisons obtained. For this reason, the SWARA method is much less used in the literature than the two previously mentioned methods (the AHP and DEMATEL), which is evident from [96][97][98][99][100][101][102][103][104][105][106][107][108][109][110][111][112][113]. The BWM is the method that has increasingly been applied over a short time .…”

Section: Review Of Applications Of Subjective Mcdm Methods In Differementioning

confidence: 99%

A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM)

2018

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In this paper, a new multi-criteria problem solving method—the Full Consistency Method (FUCOM)—is proposed. The model implies the definition of two groups of constraints that need to satisfy the optimal values of weight coefficients. The first group of constraints is the condition that the relations of the weight coefficients of criteria should be equal to the comparative priorities of the criteria. The second group of constraints is defined on the basis of the conditions of mathematical transitivity. After defining the constraints and solving the model, in addition to optimal weight values, a deviation from full consistency (DFC) is obtained. The degree of DFC is the deviation value of the obtained weight coefficients from the estimated comparative priorities of the criteria. In addition, DFC is also the reliability confirmation of the obtained weights of criteria. In order to illustrate the proposed model and evaluate its performance, FUCOM was tested on several numerical examples from the literature. The model validation was performed by comparing it with the other subjective models (the Best Worst Method (BWM) and Analytic Hierarchy Process (AHP)), based on the pairwise comparisons of the criteria and the validation of the results by using DFC. The results show that FUCOM provides better results than the BWM and AHP methods, when the relation between consistency and the required number of the comparisons of the criteria are taken into consideration. The main advantages of FUCOM in relation to the existing multi-criteria decision-making (MCDM) methods are as follows: (1) a significantly smaller number of pairwise comparisons (only n − 1), (2) a consistent pairwise comparison of criteria, and (3) the calculation of the reliable values of criteria weight coefficients, which contribute to rational judgment.

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Section: Review Of Applications Of Subjective Mcdm Methods In Differementioning

confidence: 99%

A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM)

2018

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“…Dahooie et al [51] applied a novel approach considering SWARA-ARAS method using interval-valued fuzzy sets for evaluation of oil and gas well drilling projects. Dahooie et al [52] applied the SWARA-ARAS-G approach in a competency-based IT personnel selection problem.…”

Section: Survey On Applications and Developments Of The Swara Methodsmentioning

confidence: 99%

Renewable Energy Technology Selection Problem Using Integrated H-SWARA-MULTIMOORA Approach

Maghsoodi

Mosavi

et al. 2018

Sustainability

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Due to the adaptation of recent pollution mitigation and justification policies there has been a growing trend for electricity generation from various renewable resources. The selection of the optimal renewable energy technology could be measured as a complex problem due to the complication of forthcoming circumstances in any country. Consequently, the proposed similar complex assessment problem can be tackled with the support of Multiple Attribute Decision Making (MADM) methods. The current research study investigates a technology selection problem by proposing a hybrid MADM approach based on the Step-Wise Weight Assessment Ratio Analysis (SWARA) approach with a hierarchical arrangement combined with the Multi-Objective Optimization on the basis of Ratio Analysis plus the full MULTIplicative form (MULTIMOORA). Ultimately, a conceptual case study regarding the selection of the optimal renewable energy technology based on a conceptual development project in Iran has been examined by the proposed combinative MADM methodology.

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“…Qin et al [71] introduced some hesitant fuzzy aggregation operators based on Frank triangular norms for implementation in human resource selection. Heidary Dahooie et al [2] presented a competency framework to select the best information technology expert by integrating two MCDM methods, SWARA and grey ARAS. Efe and Kurt [72] presented a possibility-degree-based TOPSIS method using interval type-2 trapezoidal fuzzy numbers for the personnel selection problem in an assembly line of a textile firm.…”

Section: Introductionmentioning

confidence: 99%

Application of the Fuzzy CODAS Method Based on Fuzzy Envelopes for Hesitant Fuzzy Linguistic Term Sets: A Case Study on a Personnel Selection Problem

Yalçın

Pehlivan

2019

Symmetry

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Fuzzy multi-criteria decision-making (MCDM) methods are useful and reliable for multi-criteria selection problems under uncertain and imprecise situations. In these methods, if decision-makers hesitate among several linguistic terms, hesitant fuzzy linguistic term sets (HFLTSs), represented by a set of successive linguistic terms instead of single linguistic terms, may be more appropriate to make evaluations. The notion of a fuzzy envelope for the HFLTSs is a beneficial tool that can be directly applied to fuzzy MCDM methods to elicit comparative linguistic expressions (CLEs). The aim of this study is to present a methodology that combines the fuzzy CODAS (COmbinative Distance-based Assessment) method with the fuzzy envelope of HFLTs based on CLEs to solve a personnel selection problem. In order to examine the feasibility of the presented methodology, a case study on blue-collar personnel selection in a manufacturing firm is conducted. A sensitivity analysis is performed to demonstrate the stability and validity of the ranking results. Furthermore, the ranking results of the presented methodology are compared with various fuzzy MCDM methods, including fuzzy EDAS, fuzzy TOPSIS, fuzzy WASPAS, fuzzy ARAS, and fuzzy COPRAS. The results show that the presented methodology is efficient and stable for solving personnel selection problems in a hesitant fuzzy environment.

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Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology

Cited by 98 publications

References 74 publications

A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM)

A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM)

Renewable Energy Technology Selection Problem Using Integrated H-SWARA-MULTIMOORA Approach

Application of the Fuzzy CODAS Method Based on Fuzzy Envelopes for Hesitant Fuzzy Linguistic Term Sets: A Case Study on a Personnel Selection Problem

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