https://valerioficcadenti.com/authors/vincenzo-scardigno/Vincenzo ScardignoHugo Blox Builder (https://hugoblox.com)en-ushttps://valerioficcadenti.com/media/icon_huef8cf56cc73f48d41a5f1ecba5605ab4_269363_512x512_fill_lanczos_center_3.pnghttps://valerioficcadenti.com/authors/vincenzo-scardigno/https://valerioficcadenti.com/talks/euro_2025_mobility/Mon, 23 Jun 2025 00:00:00 +0000https://valerioficcadenti.com/talks/euro_2025_mobility/<p><strong>Event:</strong> <a href="https://www.euro2025leeds.com/" target="_blank" rel="noopener">EURO 2025 - 32nd European Conference on Operational Research</a><br> <strong>Location:</strong> Leeds, United Kingdom<br> <strong>Date:</strong> June 23-25, 2025</p> <hr> <p>This presentation introduces a novel Markov chain analysis of academic mobility patterns revealing how university reputation influences researchers&rsquo; career trajectories and institutional barriers to mobility.</p> <p>This presentation explores the complex dynamics of international academic mobility using advanced Markov chain modelling to analyse career trajectories of researchers across different university rankings and institutional affiliations.</p> <p><strong>Research Objectives:</strong></p> <ul> <li><strong>Institutional Barriers:</strong> Investigate how university reputation creates mobility barriers for researchers</li> <li><strong>Career Trajectories:</strong> Analyse the influence of initial institutional affiliation on career development</li> <li><strong>Global Patterns:</strong> Understand international mobility patterns across different university rankings</li> <li><strong>Policy Implications:</strong> Provide insights for addressing mobility inequalities in academia</li> </ul> <p><strong>Methodology:</strong></p> <ul> <li><strong>Large-Scale Data:</strong> Analysis of 3.8+ million individual records from ORCID database</li> <li><strong>University Rankings:</strong> Global ranking system to classify institutional standing</li> <li><strong>Markov Chain Modelling:</strong> Transition probability analysis for inter-institutional mobility</li> <li><strong>Longitudinal Analysis:</strong> Year-by-year career tracking and trajectory modelling</li> </ul> <p><strong>Key Findings:</strong></p> <ul> <li><strong>Mobility Constraints:</strong> Evidence of significant barriers between high and low-ranked institutions</li> <li><strong>Career Persistence:</strong> Strong influence of initial institutional affiliation on career development</li> <li><strong>Transition Patterns:</strong> Systematic analysis of movement probabilities across university rankings</li> <li><strong>Global Inequalities:</strong> Documentation of institutional hierarchies affecting researcher mobility</li> </ul> <p><strong>Data and Methods:</strong></p> <ul> <li><strong>ORCID Database:</strong> Comprehensive researcher career tracking across millions of academics</li> <li><strong>Ranking Integration:</strong> Global university ranking data for institutional classification</li> <li><strong>Statistical Framework:</strong> Markov chain transition matrices and probability analysis</li> <li><strong>Temporal Analysis:</strong> Multi-year career progression and mobility patterns</li> </ul> <p><strong>Academic Impact:</strong> This research contributes to understanding systemic inequalities in academic career development and provides empirical evidence for policy interventions to improve researcher mobility and career equity across institutional hierarchies.</p> <p><strong>Collaborative Research:</strong> Joint work with Vincenzo Scardigno, demonstrating interdisciplinary collaboration in applying quantitative methods to higher education research and academic career analysis.</p>https://valerioficcadenti.com/authors/vincenzo-scardigno/Mon, 01 Jan 0001 00:00:00 +0000https://valerioficcadenti.com/authors/vincenzo-scardigno/