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Dr Igor Menezes

Biography Igor Menezes is a psychometrician and senior lecturer (associate professor) in OBHRM and People Analytics in the Hull University Business School. He is the programme director for the MSc in People Analytics and leader of the People Analytics and Psychometrics Laboratory. He is a BPS Chartered Psychologist, Division of Occupational Psychology, Mathematical, Statistical & Computing Psychology Section and Fellow of the Advance HE / FHEA.

He carried out his postdoctoral studies at the University of Cambridge, from 2013 to 2014, working on the implementation of multidimensional item response theory into the Concerto platform, and from 2016 to 2017, working on a project in partnership with BOSTES/NESA, Australia, to test new algorithms from machine learning and modern psychometric techniques in order to improve the standards of achievement in NSW schools.

His research interests include the development and validation of psychometric instruments to measure psychological constructs in different fields (e.g., healthcare, education, recruitment and selection, personality and team dynamics) and the combination of machine learning and psychometric techniques to investigate relationships between organisational behaviours as complex systems.

He is accepting PhD students interested in an evidence-based approach to the study of people analytics and in the development and application of psychometric models and machine learning algorithms to the investigation of micro- (e.g., organisational commitment, organisational climate, organisational engagement, turnover intentions, wellbeing etc) and meso-organisational behaviours (e.g., agile team dynamics).
Research Interests Development and validation of psychometric instruments
People Analytics
Micro-organisational behaviours (e.g., organisational commitment, organisational citizenship behaviours, employee turnover etc)
Meso-organisational behaviours (e.g., agile team dynamics)
Individual differences (e.g., Personality  and Personal Values)
Psychological networks and complex systems
Scopus Author ID 57208579581