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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Retraction Note: A New Extended VIKOR Approach Using q-Rung Orthopair Fuzzy Sets for Sustainable Enterprise Risk Management Assessment in Manufacturing Small and Medium-Sized Enterprises

2025 , Sun Cheng , Sun Jianfu , Melfi Alrasheedi , Saeidi, Parvaneh , Arunodaya Raj Mishra , Pratibha Rani

The Editor-in-Chief and the publisher have retracted this article. The article was submitted to be part of a guest-edited issue. An investigation by the publisher found a number of articles, including this one, with a number of concerns, including but not limited to compromised editorial handling and peer review process, inappropriate or irrelevant references or not being in scope of the journal or guest-edited issue. Based on the investigation’s findings the Editor-in-Chief therefore no longer has confidence in the results and conclusions of this article. The authors disagree with this retraction.

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Decision support framework for healthcare waste disposal techniques assessment using an integrated picture fuzzy gained and lost dominance score-based approach

2024 , Arunodaya Raj Mishra , Pratibha Rani , Saeidi, Parvaneh , Adel Fahad Alrasheedi , Ahmad M. Alshamrani

Improper management of healthcare wastes can lead to severe health hazard and environmental pollution such as water, air and soil. Selection of the suitable disposal technique requires consideration of multiple alternatives and evaluation criteria. Multi-criteria decision-making frameworks can be appropriate to handle the decision-making problem of healthcare waste disposal techniques assessment. However, uncertainty is inherently appeared in the assessment of such types of real-life applications. To this aim, the present work develops a hybrid picture fuzzy group decision-making framework and applies to assess healthcare waste disposal techniques based on various criteria and uncertainty perspective. In this regard, we introduce a new distance measure for picture fuzzy sets and further use to find the decision experts’ weights. The proposed measure can overwhelm the shortcomings of some of the previously introduced picture fuzzy distance measures. Based on the proposed measure, we further present an improved maximizing deviation model to derive the weight of criteria in the picture fuzzy environment. Further, we introduce a hybrid gained and lost dominance score method by incorporating the proposed distance measure-based weighting model for experts' weights and maximizing deviation method-based criteria weights. The developed framework considers the dominance relations between options and provides more efficient outcomes in the assessment of group decision-making problems. Finally, the developed method is applied to an empirical study of healthcare waste disposal techniques assessment problem, which illustrates the usefulness of introduced framework. Sensitivity analysis is performed to test different scenarios related to the proposed approach, which demonstrates the robustness of determined outcomes. Comparison with existing studies is discussed to show the robustness of the developed group decision-making framework. The present work contributes to the field of decision support through which the policymakers can take responsible decisions in the healthcare industry.

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Fermatean fuzzy score function and distance measure based group decision making framework for household waste recycling plant location selection

2024 , Arunodaya Raj Mishra , Pratibha Rani , Parvaneh Saeidi , Muhammet Deveci , Adel Fahad Alrasheedi

The household waste (HW) disposal and recycling have become a significant challenge due to increasing quantities of generated household wastes and increased levels of urbanization. Selecting locations/sites for building new HW recycling plant comprises numerous sustainability dimensions, thus, this work aims to develop new decision-making model for evaluating and prioritizing the HW recycling plant locations. This paper is categorized into three phases. First, we propose new improved score function to compare the Fermatean fuzzy numbers. Moreover, an example is presented to validate the effectiveness of proposed score function over the extant ones. Second, we introduce new distance measure to estimate the discrimination degree between Fermatean fuzzy sets (FFSs) and further discuss its advantages over the prior developed Fermatean fuzzy distance measures. Third, we introduce an integrated methodology by combining the method with the removal effects of criteria (MEREC), the stepwise weight assessment ratio analysis (SWARA) and the measurement alternatives and the ranking according to compromise solution (MARCOS) approaches with Fermatean fuzzy (FF) information, and named as the “FF-MEREC-SWARA-MARCOS” framework. In this method, the FF-distance measure is used to find the weights of involved decision-making experts. Moreover, an integrated criteria weighting method is presented with the combination of MEREC and SWARA models under the context of FFSs, while the combined FF-MEREC-SWARA-MARCOS model is applied to evaluate and prioritize the locations for HW recycling plant development, which illustrates its feasibility of the developed framework. Comparative study and sensitivity assessment are conducted to validate the obtained outcomes. This work provides a hybrid decision analysis approach, which marks a significant impact to the HW recycling plant location selection process with uncertain information.

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