Staff profile

Dr Riccardo Mogre is an Associate Professor in Operations Management and a Fellow of the Durham Energy Institute. In 2022/2023, Riccardo is on research leave from Durham. He is joining the MIT Operations Research Center and the Sloan School of Management as a Fulbright Scholar and The University of Auckland Department of Statistics as a Royal Society of New Zealand Catalyst Fund Awardee.

His research focuses on how to make management decisions in presence of risks with applications in manufacturing, services, and supply chains. His current research interests include:

• Dynamic expediting to manage delays in manufacturing, projects, and supply chains.
• Price and lead-time quotation in manufacturing and services in presence of uncertainty.
• Disruption and delay mitigation in global supply chains.

In his research he uses operations research techniques, such as Markov decision processes, queueing theory, and discrete event simulation. His research has been funded by the Charles Wilson Award, the Royal Society of New Zealand, the US-UK Fulbright-Lloyds Scholar award, INFORMS, ESRC, Research England, the EU, the White Rose Consortium, and the Technology Strategy Board.

At Durham, Riccardo is faculty representative at the University Senate Committee for Wider Student Experience. He was co-director of the Centre of Innovation of Technology Management with responsibility for its Business Analytics stream. He was also director of the MSc in Business Analytics, an interdisciplinary programme that he jointly created with the Computer Science department, and the Durham-EBS Executive MBA. At Durham he has been teaching courses on Business Analytics, Decision Making, and Project Management, primarily to MBA students. He was also the academic advisor of the Analytics and Operational Research Student Society.

Mini Biography

Dr Riccardo Mogre is an Associate Professor in Operations Management and a Fellow of the Durham Energy Institute. His research focuses on how to make management decisions in presence of risks with applications in manufacturing, services, and supply chains.

• Operations Management
• Supply Chain Management
• Stochastic Models
• Operations Research

• Innovation and Technology Management
• Management & Marketing Department

Journal Article

• Bertazzi, Luca, Mogre, Riccardo & Trichakis, Nikolaos (2023). Dynamic Project Expediting: A Stochastic Shortest-Path Approach. Management Science
• Bertazzi, L. & Mogre, R. (2018). Dynamic expediting of an urgent order with uncertain progress. European Journal of Operational Research 267(1): 78-85.
• Mogre, R., Talluri, S. & D’Amico, F. (2016). A decision framework to mitigate supply chain risks: an application in the offshore-wind industry. IEEE Transactions on Engineering Management 63(3): 316-325.
• Mogre, R., Wong, C.Y. & Lalwani, C.S. (2014). Mitigating supply and production uncertainties with dynamic scheduling using real-time transport information. International Journal of Production Research 52(17): 5223-5235.
• Micheli, G., Mogre, R. & Perego, A. (2014). How to choose mitigation measures for supply chain risks. International Journal of Production Research 52(1): 117-129.
• Evangelista, P., Mogre, R., Perego, A., Raspagliesi, A. & Sweeney, E. (2012). A survey based analysis of IT adoption and 3PLs' performance. Supply Chain Management 17(2): 172-186.