Dr Ioannis Fragkos

Ioannis Fragkos

Associate Professor
Rotterdam School of Management (RSM)
Erasmus University Rotterdam

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Ioannis Fragkos is Associate Professor in the Department of Technology and Operations Management, within the Rotterdam School of Management (RSM). Before joining RSM, Ioannis was an instructor at University College London, teaching staff at London Business School and London School of Economics, and a research scientist with the Department of Logistics and Operations Management at HEC Montreal.


Ioannis’s research focuses on decision analytics, decision support systems and the development of large-scale optimization models. His research has appeared in leading international academic journals, and has been applied in a variety of companies in the high-tech, maritime, transportation and education industries. Ioannis has collaborated with organizations such as the UK Department for Transport, Network Rail, the Noble Group, and London Business School. He is a regular speaker at international conferences in the area of decision analytics, operations management and management science, and a member of the Institute for Operations Research and Management Science (INFORMS).








  • Academic (10)
    • Fragkos, I., Cordeau, JF., & Jans, R. (2021). Decomposition Methods for Large-Scale Network Expansion Problems. Transportation Research. Part B, Methodological, 144, 60-80. https://doi.org/10.1016/j.trb.2020.12.002

    • Wagenaar, J., Fragkos, I., & Zuidwijk, R. (2021). Integrated planning for multimodal networks with disruptions and customer service requirements. Transportation Science, 55(1), 196-221. https://doi.org/10.1287/trsc.2020.1006

    • Avgerinos, E., Gokpinar, B., & Fragkos, I. (2020). The Effect of Failure on Performance over Time: The Case of Cardiac Surgery Operations. Journal of Operations Management, 66(4), 441-463. https://doi.org/10.1002/joom.1068

    • Avgerinos, E., Fragkos, I., & Huang, Y. (2020). Team Familiarity in Cardiac Surgery Operations: The Effects of Hierarchy and Failure on Team Productivity. Human Relations, 73(9), 1278-1307. https://doi.org/10.1177/0018726719857122

    • Wagenaar, J., Kroon, LG., & Fragkos, I. (2017). Rolling stock rescheduling in passenger railway transportation using dead-heading trips and adjusted passenger demand. Transportation Research. Part B, Methodological, 101, 140-161. https://doi.org/10.1016/j.trb.2017.03.013

    • De Reyck, B., Fragkos, I., Grushka-Cockayne, Y., Lichtendahl, C., Guerin, H., & Kritzer, A. (2017). Vungle Inc Improves Monetization using Big-Data Analytics. Interfaces, 47(5), 454-466. https://doi.org/10.1287/inte.2017.0903

    • Fragkos, I., Degraeve, Z., & De Reyck, B. (2016). A Horizon Decomposition approach for the Capacitated Lot Sizing Problem with Setup Times. INFORMS Journal on Computing, 28(3), 465-482. https://doi.org/10.1287/ijoc.2016.0691

    • Fragkos, I., & De Reyck, B. (2016). On improving the Maritime Transshipment Operations of the Noble Group. Interfaces, 46(3), 203-217. https://doi.org/10.1287/inte.2015.0841

    • Akartunali, K., Fragkos, I., Miller, AJ., & Wu, T. (2016). Local Cuts and Two-Period Convex Hull Closures for Big-Bucket Lot-Sizing Problems. INFORMS Journal on Computing, 28(4), 766-780. https://doi.org/10.1287/ijoc.2016.0712

    • Alexandre de Araujo, S., De Reyck, B., Degraeve, Z., Fragkos, I., & Jans, RF. (2015). Period Decompositions for the Capacitated Lot Sizing Problem with Setup Times. INFORMS Journal on Computing, 27(3), 431-448. https://doi.org/10.1287/ijoc.2014.0636

  • Professional (1)
    • De Reyck, B., Grushka-Cockayne, Y., Fragkos, I., Harrison, J., & Read, D. D. (2017). Optimism Bias Study: Recommended Adjustments to Optimism Bias Uplifts. UK Department for Transport.

  • Popular (2)
    • Huang, Y. (Author), Avgerinos, E. (Author), & Fragkos, I. (Author). (2020). 18 Minutes, 37 Seconds: Improving The Effectiveness Of Surgical Teams (Part 2). Web publication/site, COUNCIL ON BUSINESS & SOCIETY INSIGHTS.

    • Huang, Y. (Author), Avgerinos, E. (Author), & Fragkos, I. (Author). (2020). Improving the effectiveness of surgical teams. Web publication/site, COUNCIL ON BUSINESS & SOCIETY INSIGHTS.


Media items

  • How to help healthcare staff bounce back after the pandemic

    Healthcare staff are working relentlessly under heavy psychological and physical distress caused by the COVID-19 pandemic. However, new research from the RSM, Erasmus University shows consistency in healthcare teams increases…

  • What makes surgical teams more productive?

    An article about the research of Ioannis Fragkos, Professor in the Department of Technology and Operations Management, within the RSM. The article adresses the problem within the focus of many govenrments: healthcare service.…

  • New research into productivity could allow surgeons to perform an extra 53 operations a year

    Research to which Ioannis Fragkos of RSM conducted to has found that organising surgical teams based on ‘horizontal familiarity’ – such as surgeons working with other surgeons that they are familiar with, and sub-team members…

Discovery items

Moving forward after surgical failure

Healthcare teams work better together if they’re familiar – particularly after a patient death. And later patients leave hospital faster.


Decision Science & Operations

  • Study year: 2021/2022, 2020/2021, 2019/2020
  • Code: BM27MIM
  • ECTS: 6 Level: Master

Research Methods and Skills

  • Study year: 2021/2022, 2020/2021
  • Code: BMRM3SCM
  • Level: Master

Past courses

Management science

  • Study year: 2018/2019, 2017/2018, 2016/2017, 2015/2016
  • Code: BM14MIM
  • ECTS: 2 Level: Master

Operations Research Methods

  • Study year: 2018/2019, 2017/2018, 2016/2017, 2015/2016
  • Code: BMRM1SCM
  • ECTS: 3 Level: Master