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Showing 2 results for Mohammadi Ardakani
Dr Shabnam Mohammadi Ardakani, Dr Hamid Babaei Meybodi,
Volume 15, Issue 2 (12-2024)
Abstract
With the expansion of emerging technologies, their applications have been introduced as a transformative factor in many industries and fields. However, these developments require more research in the area of new technologies. Nevertheless, few studies have comprehensively examined the published research in this field. In this regard, bibliometric studies, as one of the effective research methods in the field of emerging technologies, are a practical and effective tool in identifying research patterns, knowledge flows, study content, and key terms. Using this method, one can understand and briefly examine the scientific foundations and impact of emerging technologies. In summary, conducting bibliometrics in the field of emerging technologies can be used as an effective tool in identifying and analyzing research paths and the development of advanced technologies. In this context, articles published in the field of emerging technologies in the period 2013-2023 in various fields have been examined. The required data includes 13,263 articles extracted from the WOS database and were analyzed using Biblioshiny software under R-package. The obtained results include identifying influential authors, leading journals, organizations, and countries related to the field of emerging technologies. Additionally, using precise bibliometric analysis tools, the authors' collaboration network, thematic trends, most common terms, and citation network have been extracted. Finally, with the help of network analysis, key clusters in the existing literature have been identified based on research areas of new technologies.
Hamid Babei Meybodi, Shabnam Mohammadi Ardakani, Hossein Ghaneai,
Volume 17, Issue 1 (5-2026)
Abstract
Effective management, as one of the central pillars of organizational success, hinges on the ability to make informed decisions by appropriately combining and coordinating various elements to achieve desired objectives. In decision-making processes, especially in complex scenarios, decision-makers often rely on a multitude of factors to arrive at the most suitable conclusion. This is particularly true in multi-criteria decision-making (MCDM), where decisions are based on evaluating several criteria rather than a single measure of optimality. The growing body of research over recent decades has delved deeply into MCDM methodologies, yet one fundamental aspect remains: the varying significance of the criteria involved. It is critical to accurately determine the weight or importance of each criterion to ensure optimal decision outcomes.
In this paper, we introduce a novel weighting technique designed to address the challenges of assigning weights in MCDM problems, called the Dispersion-based Weighting Method (DWM). This method builds upon the principles of statistical dispersion and offers an efficient alternative to traditional entropy-based weighting methods. The process involves constructing a criterion matrix, followed by the calculation of the mean, standard deviation, and coefficient of variation for each criterion. The weights are then computed based on these statistical measures, providing a robust and straightforward approach for determining the relative importance of each criterion.
To validate the proposed DWM technique, several numerical examples are presented, demonstrating its practical application and effectiveness. Additionally, we compare the results obtained using DWM with those derived from the well-established Shannon entropy method, which is widely used in MCDM applications. The comparative analysis reveals a strong correlation between the two techniques, while highlighting the advantages of the DWM approach, including:
The findings suggest that DWM offers a more accessible, efficient, and versatile alternative to traditional methods, particularly in situations where computational efficiency and handling of diverse data types are crucial.
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