Jianyu CHEN

Social Scientist in People-Environment studies & Behavioural modelling
Social, Economic and Geographical Sciences
T: +44 (0)344 928 5428
Jianyu Chen is a social scientist in people-environment studies and behavioural modelling in the Department of Social, Economic and Geographical Sciences (SEGS) at the James Hutton Institute (Aberdeen) . His current research interests include socio-spatial representations of individuals, pro-environment attitudes and behaviours, and the "Green Economy", such as social representations of "circular economy".

Prior to this James Hutton, Jianyu worked as a postdoctoral researcher at the LabEx IMU (Intelligence des Mondes Urbains) and the GRePS of the University Lumière Lyon 2, where he explored spatial representations of inhabitants living in peri-urban industrial territories in southern Lyon.

Jianyu obtained his PhD in late 2021 from the University of Strasbourg (France) and Luxembourg Institute of Socio-Economic Research (LISER) with an interdisciplinary background in Social Psychology and Urban Geography, where he studied various mobility behaviours of Franco-Luxembourgish cross-border commuters through Social Representations Theory.


Ongoing research projects

Jianyu is currently working on a project related to the Circular Economy in Scotland, which aims to gain a deeper understanding of the current state of the Circular Economy in Scottish society. He is conducting research at the individual and household level to examine the evolution of pro-environmental attitudes and behaviours among Scottish people over the past several decades, using data from the UK Household Longitudinal Survey.  He also explores on how Social Representations Theory offers a framework for understanding the way in which different groups internalise the same ideal categories (notably the Circular Economy), how their particular system of attitudes, beliefs or symbols renders the perceived information meaningful, communicable and actionable.


Research approaches

Jianyu employs a mixed methodology approach in his research, utilizing both quantitative and qualitative methods. He has developed expertise in working with longitudinal population census data and aims to integrate macro-level statistical quantitative data with micro-level interpretive qualitative data through the use of a relational quantitative analysis interface, such as factorial analysis (e.g. Multiple Correspondence Analysis).


Technical / contract reports

Conference posters / abstracts