Institutional affiliations, network dynamics and the influence of European Union framework programs as drivers for Nobel Prizes success
Daniele Bregoli, Martina Giurato, Marco Ciro Liscio, Gagan Narang, Paolo SospiroPurpose
The Nobel Prize is widely regarded as the pinnacle of scientific, literary and humanitarian achievement; yet, the institutional and funding mechanisms associated with this recognition remain poorly understood. This study examines how institutional affiliations, collaboration networks and major public research funding programmes are associated with Nobel Prize outcomes.
Design/methodology/approach
The study develops a data-driven framework that integrates large-scale structured datasets with publicly available biographical information on institutional affiliations, doctoral training, nominations and geographic trajectories. The resulting dataset comprises 20,126 nominations, 963 laureates and extensive institutional linkages. Statistical testing, network analysis, changepoint detection, time series modeling and institutional effectiveness indicators, including prizes per nomination, are used to identify institutional and temporal patterns.
Findings
Results show a significant association between university affiliations and Nobel recognition, with marked differences in institutional effectiveness. Temporal analyses reveal structural shifts in affiliation patterns over time. Evaluation of the European Framework Programmes, particularly Horizon initiatives, indicates increased Nobel activity after 2014, following a prolonged period of stagnation. The findings highlight the importance of institutional environments, geographic concentration and sustained research funding in supporting scientific excellence.
Originality/value
This study integrates nomination-level data, institutional networks, statistical modeling and funding programme analysis within a unified empirical framework. By linking Nobel outcomes to institutional, geographic and policy contexts, it provides a comprehensive perspective on the factors associated with scientific excellence.