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Education and Research Awards 2025 |
| Research Paper of the Year |
This award celebrates nominees who have advanced the theory, knowledge and practice of project management through a published academic paper.
To be eligible to enter this category the research paper must have been published (i.e. not online first or early cite) in a peer-reviewed journal in 2024. Blogs will not be accepted. To check a journal is peer reviewed search on the Master Journal List mjl.clarivate.com. A research paper can only be entered into this category once. Entrants can be members or non-members of APM, from both in and outside of the UK.
Entries should take the form of a 1,000-word personal statement (in English) addressing the criteria below, accompanied by the published research paper in pdf format.
Congratulations and good luck to all our finalists...
Finalist | Carolina M. Zani, Juliano Denicol, Tim Broyd, School of Sustainable Construction, The Bartlett Faculty of the Built Environment, University College London - Organisation design in megaprojects: A systematic literature review and research agenda
Megaprojects have a complex and evolving web of organisations arranged in a multilevel and multiphase structure, with intra- and inter-organisational boundaries evolving during the life cycle.
This systematic review explores organisation design in megaprojects, identifying the processes for designing temporary megaproject organisational systems. This is the world’s largest review conducted in the field, which analyses 141 full articles from a sample of 10,078 papers.
Finalist | David Oyekunle, Ugochukwu Okwudili Matthew, David Preston, David Boohene, Salford Business School, University of Salford, Computer Science Department, Federal University (Brazil), Department of Entrepreneurship and Business Science, University of Energy and Natural Resources (Ghana) - Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects
This multidisciplinary study explores how artificial intelligence (AI) systems influence client confidence using a mixed-methods approach.
Through structural equation modelling (SEM) of 1,248 participants, the study examines technological, psychological, and organizational factors affecting AI adoption highlighting perceived utility, transparency, risk, leadership endorsement, and ethical accountability. Additionally, insights from 35 interviews and five case studies reveal the role of explainability, subject matter expertise, and stakeholder engagement.
The study presents a conceptual framework to advance understanding of AI trust across industries, offering theoretical insights and practical applications for businesses and policymakers in fostering responsible AI adoption.