Researcher at Lorestan University, Iran.
Dr. Mohammad Tavassoli is a distinguished scholar in the field of Industrial Management, with a strong emphasis on Operations Management, Data Envelopment Analysis (DEA), and Supply Chain Management. He has an extensive academic background, culminating in a Postdoctoral Research position at Esfahan University, Iran, where he focused on developing a dynamic network DEA model for assessing Iran’s electricity distribution network with sustainability and resilience approaches. His Ph.D. research at Esfahan University also revolved around DEA models, incorporating fuzzy networks to evaluate Iran’s electricity distribution system. Prior to this, he earned his M.Sc. in Industrial Management from Islamic Azad University, Karaj Branch, and a B.Sc. in Industrial Engineering from Islamic Azad University, Khorramabad Branch.
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Education Background
Dr. Mohammad Tavassoli holds an extensive academic background in Industrial Management and Engineering. He earned his Postdoctoral Research degree in Industrial Management (Operations Management) from Esfahan University, Department of Management, Iran, in 2022. Prior to that, he completed his Ph.D. in Industrial Management (Operations Management) in 2021 from the same institution. His postgraduate studies include an M.Sc. in Industrial Management (Operations Management) from Islamic Azad University, Karaj Branch, Iran, in 2013, following his B.Sc. in Industrial Engineering from Islamic Azad University, Khorramabad Branch, Iran, in 2009. Dr. Tavassoli’s educational journey has equipped him with deep expertise in operations management, industrial processes, and management strategies, contributing significantly to academia and industry.
Professional Development
Dr. Tavassoli is an experienced educator and researcher, having taught both undergraduate and graduate courses in Operations Research, Operations Management, Decision Sciences, Integer Programming, Game Theory, Inventory Management, and Dynamic Systems. His teaching portfolio also includes specialized topics such as Data Envelopment Analysis (DEA), Multi-Criteria Decision Making (MCDM), Analytic Hierarchy Process (AHP), and Analytic Network Process (ANP). He is an active peer reviewer for several high-impact international journals, including Management Decision, Annals of Operations Research, Benchmarking: An International Journal, and Journal of the Operational Research Society, among others.
Research Focus
Dr. Tavassoli’s research expertise spans a broad range of topics within Industrial Management, including Operations Research (OR), Data Envelopment Analysis (DEA), Supply Chain Management (SCM), Resilience and Sustainable Supply Chain Management, Fuzzy Systems, Dynamic Systems, Production Management, Project Management, and Quality Management. His work extensively incorporates quantitative methodologies to enhance operational efficiency and decision-making in complex industrial systems.
Author Metrics:
Dr. Tavassoli has established himself as a prominent researcher, evidenced by his author metrics. He holds an H-index of 15 and an i10-index of 19, reflecting his impactful contributions to academia through numerous peer-reviewed publications.
Honors & Awards
Dr. Tavassoli’s outstanding contributions to Operations Management and Industrial Research have earned him recognition in both academic and professional circles. He is an active member of prestigious organizations, including the Institute for Operations Research and Management Sciences (INFORMS), the Australian Society for Operations Research (ASOR), the International Society on Multiple Criteria Decision Making, the Association of European Operational Research Societies (EURO), and the International Data Envelopment Analysis Society (iDEAs). His affiliations with these organizations underscore his commitment to advancing research and knowledge dissemination in the fields of industrial management and operational research.
Publication Top Notes
1. A New Fuzzy Network Data Envelopment Analysis Model for Measuring Efficiency and Effectiveness: Assessing the Sustainability of Railways
- Journal: Applied Intelligence
- Volume: 52 (12), Pages: 13634-13658
- Year: 2022
- Citations: 15
- Key Contribution: Developed a fuzzy network DEA model to assess the efficiency and effectiveness of railway systems from a sustainability perspective.
2. Sustainability Measurement of Combined Cycle Power Plants: A Novel Fuzzy Network Data Envelopment Analysis Model
- Journal: Annals of Operations Research
- Year: 2023
- Citations: 12
- Key Contribution: Proposed an innovative fuzzy network DEA model to measure the sustainability of combined cycle power plants, considering environmental and operational performance.
3. A Stochastic Data Envelopment Analysis Approach for Multi-Criteria ABC Inventory Classification
- Journal: Journal of Industrial and Production Engineering
- Volume: 39 (6), Pages: 415-429
- Year: 2022
- Citations: 11
- Key Contribution: Introduced a stochastic DEA-based model for multi-criteria ABC inventory classification, optimizing stock management under uncertainty.
4. Estimating Most Productive Scale Size Decomposition in a Fuzzy Network Data Envelopment Analysis Model: Assessing the Sustainability and Resilience of the Supply Chain
- Journal: RAIRO-Operations Research
- Volume: 58 (2), Pages: 1807-1833
- Year: 2024
- Citations: 1
- Key Contribution: Utilized fuzzy network DEA to measure supply chain sustainability and resilience, identifying the most productive operational scale.
5. A Multiplier Form of Slacks-Based Measure Model in Stochastic Data Envelopment Analysis
- Journal: International Journal of Management and Decision Making
- Volume: 21 (3), Pages: 243-261
- Year: 2022
- Citations: 2
- Key Contribution: Developed a multiplier-based slacks-based measure (SBM) model to improve stochastic DEA performance evaluation.
6. Assessing Sustainability of Suppliers: A Novel Stochastic-Fuzzy DEA Model
- Authors: Farzipoor Saen, R. & Zanjirani, DM
- Year: 2020
- Citations: 2
- Key Contribution: Created a stochastic-fuzzy DEA approach for evaluating supplier sustainability, balancing uncertainty and efficiency analysis
Conclusion
Dr. Mohammad Tavassoli is highly deserving of the Best Researcher Award due to his significant contributions to Data Envelopment Analysis, Operations Research, and Sustainability Modeling. His research is both theoretically innovative and practically impactful, with a strong publication record, academic recognition, and contributions to knowledge dissemination.
While he has already made remarkable contributions, further international collaborations and industrial applications could enhance his global research influence. Nonetheless, his expertise and impact make him an excellent candidate for the award.