Mehtap Dursun

Papers

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About

Mehtap Dursun’s research lies at the intersection of decision-making under uncertainty, industrial automation, and digital supply chain management. Her most cited work, “Robot selection using a fuzzy regression-based decision-making approach” (2011, 34 citations), addresses a critical challenge in advanced manufacturing: evaluating industrial robots based on multiple, often conflicting criteria. By integrating fuzzy logic with regression analysis, Dursun provided a robust framework for selecting automation technologies that enhance product quality and cost-efficiency—a contribution that remains foundational for researchers in production engineering. More recently, her paper “Digital Supply Chain Agility Analysis Using IFTOPSIS Method” (2020, 13 citations) extends her expertise into Industry 4.0, where she applies intuitionistic fuzzy TOPSIS to help firms navigate digital transformation and respond to sudden disruptions. This work reflects her ability to bridge theoretical decision models with real-world industrial needs. With a career focused on fuzzy multi-criteria decision-making, Dursun has equipped practitioners and scholars alike with tools to optimize complex choices in manufacturing and logistics, solidifying her impact in operations research and supply chain analytics.