• Department Head
    Professor

    Supply Chain Management Department
    Room 630 Drake Centre
    181 Freedman Crescent
    University of Manitoba (Fort Garry Campus)
    Winnipeg, Manitoba R3T 5V4

    T: (204) 474-6870
    F: 204-474-7545

    ss.appadoo@umanitoba.ca

Biography

Professor Appadoo is a professor, and the institutional head of the Department of Supply Chain Management at the University of Manitoba, Canada. In addition to teaching undergraduate and graduate courses, he is a prolific researcher, with his work continually being published in esteemed journals (both national and international) and referred proceedings.

His tenacious and innovative research has garnered global acclaim –frequently cited by academics both domestically and internationally. Professor Appadoo has published in journals such as the European Journal of Operational Research(EJOR), Annals of Operational Research (AOR),  Fuzzy Optimization and Decision Making (FODM), International Journal of Production Economics(IJPE), and Information Science, among others.

Professor Appadoo’s work spans interdisciplinary horizons, exemplified by his partaking in collaborative projects - including working with over fifty researchers from around the world in various academic disciplines. Having published over one hundred and fifty articles in international journals and proceedings, his publications have appeared in internationally revered journals - specializing in management science and supply chain management. His articles were included in the ‘Top 25 Hottest Articles’ list for Science Direct, published by Elsevier, and were among the most cited articles on Elsevier. 

Professor Appadoo also serves on the editorial review boards for many international Journals.

Dr. Appadoo is primarily interested in developing analytics techniques and Decision-Making Systems. He is currently working on quantitative and fuzzy decision-making models, as well as multi-criteria and group decision-making. He has presented his work at prestigious conferences and research workshops, such as INFORMS Annual Meeting, ASAC, CORS Annual Meeting, IEEE, and DSI Annual Conference.

He co-authored a book titled, More-for-Less Solutions in Fuzzy Transportation Problems (Studies in Fuzziness and Soft Computing).His research is funded by the National Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant as a Principal Investigator. The Discovery Grants Program promotes and maintains a diverse base of high-quality research capabilities in Natural Science and Engineering in Canadian universities, fostering research excellence and providing a stimulating environment for dynamic research training. 

Professor Appadoo is a recipient of the Associates’ Achievement Award, the Joint UM/UMFA Committees on Merit Award, and several best paper awards at some national and international conferences.  

In addition to his academic prowess, professor Appadoo is known for his capabilities as an educator. Students commend Professor Appadoo’s teaching methodology and consistently rank his classes and instruction as exceptional.

He serves on departmental, faculty, and university committees and contributes extensively to the professional community through review processes – operating as a conference chair and academic reviewer.

Owing to Professor Appadoo's significantly contribution and efforts in creating the Ph.D. program in the Department of Supply Chain Management, the Asper School of Business is one of the limited institutions offering a Ph.D. program in SCM.

Research Interests

Theory and application of Management Science/Operations Research related to mathematical programming, application of fuzzy systems, possibility theory, and time-series models in both deterministic and fuzzy setup, GARCH modeling, inventory models, decision analysis, multi-criteria decision making, scoring models, AHP, supplier selection, TOPSIS model and its application to supply chain management.

Application of Intuitionistic fuzzy set to Multi-criteria Decision Making Problems, in which intuitionistic fuzzy sets are tools useful for modeling and processing imperfect information and imprecise knowledge.