Dr Siamak Kheybari
Management School
Lecturer in Business Analytics and Supply Chain Management
+44 114 222 3452
Full contact details
Management School
B61
91Ö±²¥ University Management School
Conduit Road
91Ö±²¥
S10 1FL
- Profile
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Dr. Siamak Kheybari is a Lecturer in Business Analytics and Supply Chain Management at the University of 91Ö±²¥. Previously, he served as a Research Associate in Industrial Systems and Network Analysis at the University of Cambridge's Institute for Manufacturing. He also gained valuable experience as a Postdoctoral Fellow at NEOMA Business School.
Siamak is an expert in decision and risk analysis, with expertise in behavioural decision research, decision modelling, and strategic decision-making. His primary research interests include behavioural decision analysis, strategic resource allocation for industry and healthcare systems, and facilitated decision modelling with a focus on digital transformation and network optimisation. His research bridges analytical methods with real-world applications to address complex challenges in supply chain management, focusing on improving system performance and adaptability.
- Qualifications
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PhD in Management- Operations Research
- Research interests
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My principal research interests focus on advancing decision analysis and strategic decision-making in complex systems. This includes behavioural decision analysis, strategic resource allocation for industry and healthcare systems, and facilitated decision modelling, particularly in the context of digital transformation and network optimization.
A key aspect of my work is risk analysis, aimed at enhancing the robustness and reliability of decisions in dynamic environments. I also investigate network configuration, optimizing interconnected systems to improve operational efficiency and adaptability while ensuring alignment with organizational objectives.
Additionally, I explore the design and optimization of digital supply chains, leveraging data-driven approaches to enhance connectivity, scalability, and responsiveness. These areas of research are unified by a commitment to developing analytical methods and practical tools that address challenges in supply chain management and help organizations navigate the complexities of decision-making.
Key Research Areas:
- Behavioural Decision Analysis
- Strategic Decision-Making
- Risk Analysis
- Network Configuration
- Digital Supply Chains
- Publications
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Journal articles
- . Group Decision and Negotiation, 33, 883-909.
- . Journal of Knowledge Management, 28(9), 2519-2547.
- . Expert Systems with Applications, 236, 121238-121238.
- . Operations Management Research, 17(1), 340-362.
- . Operations Management Research, 16(4), 2008-2024.
- . Computers & Industrial Engineering, 180, 109258-109258.
- . Operations Management Research, 16(2), 949-968.
- . Annals of Operations Research, 324(1-2), 13-36.
- . Journal of the Operational Research Society, 74(2), 509-526.
- . International Transactions in Operational Research, 30(3), 1479-1504.
- . Expert Systems with Applications, 209, 118265-118265.
- . Energy, 228, 120593-120593.
- . International Journal of Information Technology & Decision Making, 20(05), 1499-1517.
- . IEEE Transactions on Engineering Management, 68(2), 483-497.
- . Information Systems, 92, 101534-101534.
- . International Journal of Information Technology & Decision Making, 19(03), 741-773.
- . Applied Mathematics and Computation, 367, 124780-124780.
- Efficient Harvesting of Saffron Using Integer Programming. International Journal of Agricultural Management and Development, 10(3), 307-321.
- . Journal of Cleaner Production, 232, 257-265.
- . Applied Energy, 242, 612-623.
- . OPSEARCH, 56(2), 539-562.
- . Journal of Business & Industrial Marketing.
- . International Journal of Information Technology & Decision Making, 1-29.
- . Journal of Supply Chain Management Science.
Chapters
- Research group
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Operations Management and Decision Sciences (OMDS)
- Teaching activities
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- Analysis for Decision Making
- Multi-Criteria Decision Making
- Global Supply Chain Leadership
- PhD Supervision
I welcome PhD candidates who are interested in conducting quantitative research in fields that align with my research interests.