Decision support system for human resources appraisal and selection

Ruskova, N.A.

doi:10.1109/is.2002.1044281

Cited by 17 publications

(3 citation statements)

References 3 publications

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“…There are some interesting approaches in the literature which address human resource evaluation and selection in software projects using fuzzy logic. For example, Ruskova in [28] proposed a fuzzy logic-based model for human resource selection and evaluation which is divided into three modules. The first one describes the evaluation of job positions, where requirements for each job position are defined.…”

Section: Background and Literature Overviewmentioning

confidence: 99%

On Using Fuzzy Linguistic 2-Tuples for the Evaluation of Human Resource Suitability in Software Development Tasks

Gerogiannis

Rapti

Karageorgos

et al. 2015

Advances in Software Engineering

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Efficient allocation of human resources to the development tasks comprising a software project is a key challenge in software project management. To address this critical issue, a systematic human resource evaluation and selection approach can be proven helpful. In this paper, a fuzzy linguistic approach is introduced to evaluate the suitability of candidate human resources (software developers) considering their technical skills (i.e., provided skills) and the technical skills required to perform a software development task (i.e., task-related skills). The proposed approach is based on qualitative evaluations which are derived in the form of fuzzy linguistic 2-tuples from a group of decision makers (project managers). The approach applies a group/similarity degree-based aggregation technique to obtain an objective aggregation of the ratings of task-related skills and provided skills. To further analyse the suitability of each candidate developer, possible skill relationships are considered, which reflect the contribution of provided skills to the capability of learning other skills. The applicability of the approach is demonstrated and discussed through an exemplar case study scenario.

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Section: Background and Literature Overviewmentioning

confidence: 99%

On Using Fuzzy Linguistic 2-Tuples for the Evaluation of Human Resource Suitability in Software Development Tasks

Gerogiannis

Rapti

Karageorgos

et al. 2015

Advances in Software Engineering

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“…Huang et al, 2006) and (Chien & Chen, 2008) Artificial Neural Network (L. C. Huang et al, 2004)and (M. J. Huang et al, 2006) Training and Development Training Development Knowledge-based system (Liao, 2007) Expert System Rough Set Theory (Chien & Chen, 2007) Motivation Job Attitudes Performance appraisal Artificial Neural Network (Tung et al, 2005) Fuzzy logic (Ruskova, 2002) …”

Section: Personnel Selectionmentioning

confidence: 99%

Intelligent Techniques for Decision Support System in Human Resource Management

Jantan¹,

Hamdan²,

Othman³

2010

Decision Support Systems Advances In

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“…Artificial Neural Network (Tung, Huang, Chen, & Shih, 2005) Fuzzy logic (Ruskova, 2002) Administration…”

Section: Job Attitudes Performance Appraisalmentioning

confidence: 99%

Human Talent Forecasting using Data Mining Classification Techniques

Jantan

Hamdan

Othman

2010

International Journal of Technology Diffusion

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Talent management is a very crucial task and demands close attention from human resource (HR) professionals. Recently, among the challenges for HR professionals is how to manage organization’s talents, particularly to ensure the right job for the right person at the right time. Some employee’s talent patterns can be identified through existing knowledge in HR databases, which data mining can be applied to handle this issue. The hidden and useful knowledge that exists in databases can be discovered through classification task and has been widely used in many fields. However, this approach has not successfully attracted people in HR especially in talent management. In this regard, the authors attempt to present an overview of talent management problems that can be solved by using this approach. This paper uses that approach for one of the talent management tasks, i.e., predicting potential talent using previous existing knowledge. Future employee’s performances can be predicted based on past experience knowledge discovered from existing databases by using classification techniques. Finally, this study proposes a framework for talent forecasting using the potential Data Mining classification techniques.

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Decision support system for human resources appraisal and selection

Cited by 17 publications

References 3 publications

On Using Fuzzy Linguistic 2-Tuples for the Evaluation of Human Resource Suitability in Software Development Tasks

On Using Fuzzy Linguistic 2-Tuples for the Evaluation of Human Resource Suitability in Software Development Tasks

Intelligent Techniques for Decision Support System in Human Resource Management

Human Talent Forecasting using Data Mining Classification Techniques

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