Saeidi, Parvaneh
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Saeidi, Parvaneh
Main Affiliation
Quito
Email
parvanehsaeidi@uti.edu.ec
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Scopus Author ID
55252035700

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Evaluate sustainable human resource management in the manufacturing companies using an extended Pythagorean fuzzy SWARA-TOPSIS method

2022 , Saeidi, Parvaneh , Mardani, A. , Mishra, A.R. , Cajas Cajas, V.E. , Galarraga Carvajal, Mercedes

Today, organizations realized the importance of sustainability in concern with their business activities. They found out that they should focus on other aspects such as environmental and social and economic sustainability. Lately, Sustainable Human Resource Management (SHRM) is introduced as an instrument to indicate that HRM can affect the sustainable development and resource preservation of organizations. Despite that, SHRM and its related subjects are still in an emerging phase. The present study aims to propose a comprehensive approach to examine the main important factors of SHRM. To do so, a survey approach with the literature review interviewsview with experts is carried out to classify, rank, and evaluate the key SHRM factors in the manufacturing companies in Ecuador. In order to assess and prioritize the factors and the alternatives, this paper introduces a new approach using an integrated Stepwise Weight Assessment Ratio Analysis (SWARA)- Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method on the Pythagorean fuzzy sets (PFSs) setting called the PF-SWARA-TOPSIS method. To do this, we extend the SWARA method to identify and rank the SHRM factors by using PFSs. Afterward, to assess and prioritize the alternatives, this study utilizes the TOPSIS approach under PFSs. Next, to show the efficacy and applicability of the developed framework, a real case study of the SHRM problem is discussed on PFSs. Furthermore, this study performs a sensitivity investigation over diverse sets of criteria weights to illustrate the advantages of the proposed methodology. The investigation results demonstrate that the green work-life balance was ranked as the first factor by following corporate social responsibility, green employee relations, and business process redesign factors. Finally, the results of this study found that the developed approach has high efficacy and capability to handle the SHRM problem in manufacturing companies. © 2022

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Low-carbon tourism strategy evaluation and selection using interval-valued intuitionistic fuzzy additive ratio assessment approach based on similarity measures

2022 , Mishra, A.R. , Chandel, A. , Saeidi, Parvaneh

Recently, the assessment and selection of most suitable low-carbon tourism strategy has gained an extensive consideration from sustainable perspectives. Owing to participation of multiple qualitative and quantitative attributes, the low-carbon tourism strategy (LCTS) selection process can be considered as multi-criteria decision-making (MCDM) problem. As uncertainty is usually occurred in LCTSs evaluation, the theory of interval-valued intuitionistic fuzzy sets (IVIFSs) has been established as more flexible and efficient tool to model the uncertain decision-making problems. The idea of the present study is to develop an extended method using additive ratio assessment (ARAS) framework and similarity measures in a way to find an effective solution to the decision-making problems using IVIFSs. The bases of the proposed method are the IVIFSs operators, some modifications in the traditional ARAS framework and a calculation procedure of the weights of the criteria. To calculate criterion weight, new similarity measures for IVIFSs are developed aiming at the achievement of more realistic weights. Also, a comparison is demonstrated to the currently used similarity measures in order to show the efficiency of the developed approach. To confirm that the developed IVIF-ARAS approach can be successfully employed to practical decision-making problems, a case study of LCTS selection problem is considered. The final results from the developed approach and the extant models are compared for the validation of the proposed approach in this study. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.

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