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Human resources ranking in a cloud-based knowledge sharing framework using the quality control criteria

Human resources ranking in a cloud-based knowledge sharing framework using the quality control... PurposeThis paper aims to propose a new method for evaluating the quality and prioritizing of the human resources (HRs) based on trust, reputation, agility, expertise and cost criteria in the expert cloud. To evaluate some quality control (QC) factors, a model based on the SERVQUAL is used.Design/methodology/approachThe aim of this paper is to offer a fast and simple method for selecting the HRs by the customers. To achieve this goal, the ranking diagram of different HRs based on the different criteria of QC is provided. By means of this method, the customer can rapidly decide on the selection of the required HRs. By using the proposed method, the scores for various criteria are evaluated. These criteria are used in the ranking of each HR which is obtained based on the evaluation conducted by previous customers and their colleagues. First, customers were asked to select their needed criteria and then by constructing a hierarchical structure, the ranking diagram of different HRs is achieved. Using a ranking system based on evaluating the quality of the model, satisfy the customer needs to be based on the properties of HRs. Also, an analytical hierarchical process-based ranking mechanism is proposed to solve the problem of assigning weights to features for considering the interdependence between them to rank the HRs in the expert cloud.FindingsThe obtained results showed the applicability of the radar graph using a case study and also numerically obtained results showed that a hierarchical structure increases the quality and speed rating of HR ranking than the previous works.Originality/valueThe suggested ranking method in this paper allows the optimal selection due to the special needs of any given customer in the expert cloud. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Human resources ranking in a cloud-based knowledge sharing framework using the quality control criteria

Kybernetes , Volume 46 (5): 17 – May 2, 2017

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References (38)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0368-492X
DOI
10.1108/K-01-2017-0007
Publisher site
See Article on Publisher Site

Abstract

PurposeThis paper aims to propose a new method for evaluating the quality and prioritizing of the human resources (HRs) based on trust, reputation, agility, expertise and cost criteria in the expert cloud. To evaluate some quality control (QC) factors, a model based on the SERVQUAL is used.Design/methodology/approachThe aim of this paper is to offer a fast and simple method for selecting the HRs by the customers. To achieve this goal, the ranking diagram of different HRs based on the different criteria of QC is provided. By means of this method, the customer can rapidly decide on the selection of the required HRs. By using the proposed method, the scores for various criteria are evaluated. These criteria are used in the ranking of each HR which is obtained based on the evaluation conducted by previous customers and their colleagues. First, customers were asked to select their needed criteria and then by constructing a hierarchical structure, the ranking diagram of different HRs is achieved. Using a ranking system based on evaluating the quality of the model, satisfy the customer needs to be based on the properties of HRs. Also, an analytical hierarchical process-based ranking mechanism is proposed to solve the problem of assigning weights to features for considering the interdependence between them to rank the HRs in the expert cloud.FindingsThe obtained results showed the applicability of the radar graph using a case study and also numerically obtained results showed that a hierarchical structure increases the quality and speed rating of HR ranking than the previous works.Originality/valueThe suggested ranking method in this paper allows the optimal selection due to the special needs of any given customer in the expert cloud.

Journal

KybernetesEmerald Publishing

Published: May 2, 2017

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