About
Our research focuses on a central theme: how to design, analyse and improve processes.
This includes processes within the traditional manufacturing and service contexts, but also within health care, the office and museums. Other areas of interest include operations strategy, supply chain management, reputation management, cyber security and major programme management.
The group undertakes field work in the US, Europe and Asia, exploring everything from the manufacture of toys in China through to health care process improvements in the UK.
Members hold editorial positions with leading journals and their work has been published in the Journal of Operations Management, Journal of Service Research, Journal of Management Studies, and Social Science and Medicine.
Our research has won a number of awards, including the Shingo Research and Professional Publication Award, best paper and most cited awards at the Journal of Operations Management and the International Journal of Operations and Production Management, and an Advanced Institute of Management (AIM) Fellowship.
Publications
Assessing and augmenting the potential for global mega-events to support sustainable urban development: a study of the Olympic Games(opens in new window)
- Journal article
- Event Management
Maintaining capital discipline in the rush to net-zero energy systems(opens in new window)
- Journal article
- iScience
Infrastructure decision preferences and the influence of social justice education(opens in new window)
- Journal article
- INFORMS Transactions on Education
Factorial validity and measurement invariance of a self-reported scale of paradoxical leadership behaviours: evidence from sport industry leaders(opens in new window)
- Journal article
- Frontiers in Psychology
The uniqueness trap(opens in new window)
- Journal article
- Harvard Business Review
Data-Driven Decisions Lab (3DL)
With more data available and computational performance always improving, the number of machine learning models has increased in the past ten years. However, we need to better understand how these models affect real-world decision making.
The Data-Driven Decisions Lab (3DL) aims to address this challenge.
People
The intellectual diversity of our group is built upon a shared commitment that research should be based on a broad, multi-disciplinary intellectual base.