Igor Menezes is a psychometrician and lecturer in OBHRM and People Analytics at Hull University Business School. He is a BPS Chartered Psychologist and Principal Practitioner member of the Association for Business Psychology.
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 but are not limited to matching modern techniques from machine learning and psychometrics in order to develop complex systems for the investigation of organizational behaviours. By seeking to approximate academia and industry, he has developed projects with companies in the UK and Latin America aimed at the assessment of behaviours in the workplace and indicators that can ultimately improve organisational performance.
He is accepting PhD students interested in the development and application of psychometric models and machine learning algorithms to the investigation of micro-organisational behaviours (e.g., organisational commitment, organisational climate, organisational engagement, turnover intentions, etc)
An evidence-based policy for improving choice in global health access through medical travel
Ruggeri, K., Ivanovic, N., Razum, J., Kácha, O., Menezes, I. G., Zafari, Z., & Garcia-Garzon, E. (2018). An evidence-based policy for improving choice in global health access through medical travel. Health Policy, 122(12), 1372-1376. https://doi.org/10.1016/j.healthpol.2018.09.017
Desirable attributes in the ideal partner: can they vary according to gender and place of residence"
Pereira Gonçalves, M., Veloso Gouveia, V., Medeiros Cavalcanti, T., de Castro Bezerra, C., Diógenes de Medeiros, É., Farias de Oliveira, G., … Silva dos Santos, W. (2018). Desirable attributes in the ideal partner: can they vary according to gender and place of residence?. Trends in psychology, 26(3), 1221-1234. https://doi.org/10.9788/TP2018.3-04Pt
Organisational psychology micro-behaviours
Cognitive analytics and machine learning
Psychometrics / quantitative methods
Organisational commitment / engagement
Organisational citizenship behaviours
Turnover intentions / reasons