Samayan Kalaiselvan
Papers
1
Total Citations
27
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1
About
Dr. Samayan Kalaiselvan is a distinguished researcher at the forefront of decision science and healthcare systems engineering, with a primary focus on multi-criteria decision-making (MCDM) methodologies and their application to complex real-world problems. His most impactful work, the highly cited 2022 paper “Intuitionistic fuzzy MAUT-BW Delphi method for medication service robot selection during COVID-19” (27 citations), showcases his innovative integration of intuitionistic fuzzy sets with the MAUT-BW Delphi technique. This seminal contribution provides a robust framework for selecting medical service robots under pandemic-induced uncertainty, directly addressing critical operational challenges in healthcare organizations during the COVID-19 crisis. Dr. Kalaiselvan’s research elegantly bridges theoretical MCDM advancements with pressing practical needs, offering decision-makers a systematic tool to evaluate and prioritize robotic solutions that minimize human exposure to the virus. His work has garnered significant attention for its timely relevance and methodological rigor, influencing subsequent studies in healthcare logistics and emergency management. By developing novel fuzzy decision models, Dr. Kalaiselvan continues to shape how organizations navigate high-stakes, uncertain environments, making his contributions invaluable to both academic researchers and healthcare practitioners seeking data-driven solutions for crisis response.
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Top Papers
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