PhD Candidate

BSc (Universität Jena), MSc (LSE), MRes (University of Cambridge)

Year of entry

2018

Supervisor

Professor Stefan Scholtes

Pathway

Operations and Technology Management

Tom Pape

Biography

Tom has worked part-time for the regional NHS Healthcare Public Health team since the beginning of the pandemic, initially contributing to COVID-19 modelling and later pivoting towards data analytics projects on elective recovery, mental health and primary care. Before joining the doctoral programme, Tom worked as Knowledge Transfer Associate at Surrey County Council informing local bus planning, and helped University College London Hospitals as Research Associate to develop a ward performance measurement scheme. As part of his academic training, Tom has designed and delivered various lectures to EMBA and mini-MBA students at an equivalent of one module.

Research interests

Tom’s current projects seek to identify operations management solutions to reduce healthcare inequities (with NHS East of England) and try to understand what is a good size for a primary care practice to be operationally efficient (with the Health Foundation). To answer these topical questions, Tom applies causal statistical methods to routinely collected patient-level data.

Tom Pape is a member of the Operations and Technology Management subject group.

Publications and papers

Journal articles

Vindrola-Padros, C., Pape, T., Utley, M. and Fulop, N.J. (2017) “The role of embedded research in quality improvement: a narrative review.” BMJ Quality and Safety, 26(1): 70-80 (DOI: 10.1136/bmjqs-2015-004877)

Pape, T. (2017) “Value of agreement in decision analysis: concept, measures and application.” Computers and Operations Research, 80: 82-93 (DOI: 10.1016/j.cor.2016.11.018)

Pape, T. (2016) “Prioritising data items for business analytics: framework and application to human resources.” European Journal of Operational Research, 252(2): 687-698 (DOI: 10.1016/j.ejor.2016.01.052)

Pape, T. (2015) “Heuristics and lower bounds for the simple assembly line balancing problem type 1: overview, computational tests and improvements.” European Journal of Operational Research, 240(1): 32-42 (DOI: 10.1016/j.ejor.2014.06.023)

Working papers

Pape, T., Kavadias, S. and Sommer, S. (2022) “Decision bias in project selection: experimental evidence from the knapsack problem.”

Contact details

Tom Pape
Cambridge Judge Business School
University of Cambridge
Trumpington Street
Cambridge CB2 1AG
UK

[email protected]

@TomPapeJBS

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