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COVID 19 pandemic, which entered our lives suddenly, caused the change of our classical education system and forced higher education institutions to switch to distance education quickly. During this time, the need for a method that can comprehensively and scientifically evaluate the alternatives of videoconferencing tools to be used in distance education has emerged. This paper proposes a novel hybrid multi-criteria group decision-making (MCGDM) model by integrating the analytic hierarchy process (AHP) and the evaluation based on distance from average solution (EDAS) methodologies. The proposed model is developed with spherical fuzzy (SF) sets, which enable decision-makers (DMs) express their membership, non-membership and hesitancy degrees independently, and in a large three-dimensional spherical space. The applicability of the developed spherical fuzzy AHP EDAS is illustrated through a problem of selecting a videoconferencing tool for distance education. For this purpose, three DMs evaluate five popular videoconferencing tools, namely Zoom, Google Meet, Cisco WebEx, Skype and Microsoft with respect to six criteria, which are expanded with 32 related sub-criteria from the literature to more comprehensively handle the problem. The implications, sensitivity and comparative analyses, limitations and future research avenue are also given within the study.

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For many different types of businesses, additive manufacturing has great potential for new product and process development in many different types of businesses including automotive industry. On the other hand, there are a variety of additive manufacturing alternatives available today, each with its own unique characteristics, and selecting the most suitable one has become a necessity for relevant bodies. The evaluation of additive manufacturing alternatives can be viewed as an uncertain multi-criteria decision-making (MCDM) problem due to the potential number of criteria and candidates as well as the inherent subjectivity of various decision-experts engaging in the process. Pythagorean fuzzy sets are an extension of intuitionistic fuzzy sets that are effective in handling ambiguity and uncertainty in decision-making. This study offers an integrated fuzzy MCDM approach based on Pythagorean fuzzy sets for assessing additive manufacturing alternatives for the automotive industry. Objective significance levels of criteria are determined using the Criteria Importance Through Inter-criteria Correlation (CRITIC) technique, and additive manufacturing alternatives are prioritized using the Evaluation based on Distance from Average Solution (EDAS) method. A sensitivity analysis is performed to examine the variations against varying criterion and decision-maker weights. Moreover, a comparative analysis is conducted to validate the acquired findings.

Higher education buildings are very important lifelines and can be very vulnerable if located in a region of high seismic hazard, and estimating the performance and expected damage of these buildings from future earthquakes is very crucial to reduce the levels of physical damage and interruption of education, research, and human resource training activities. Rapid and economical preassessment of the sensitivity of these buildings will shed light to higher education managements for appropriate retrofitting and reconstruction planning. However, a seismic vulnerability assessment involves complex qualitative criteria set and there is a need for a model that can present the evaluations of experts in a quantitative, systematic and measurable form while reflecting the uncertain and fuzzy nature of the process to the model. In this paper, a novel multi-criteria decision making (MCDM) decision support model is developed by extending Additive Ratio ASsessment (ARAS) to spherical fuzzy ARAS. The applicability of the model is illustrated through a numerical example for seismic vulnerability assessment of higher education institution buildings and three decision-makers (DMs) evaluate four buildings with respect to eight criteria from the literature. Sensitivity and comparative analysis, practical implications, limitations and future research avenue are also given within the study.