Abstract
Innovation driven circular economics and technological transitions. A special emphasis will be given to composite indicators based on Multiple Criteria Decision Aiding methods. On the subsjct see Greco, S., Ishizaka, A., Tasiou, M., & Torrisi, G. (2019). On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness. Social indicators research, 141, 61-94.
Keywords
artificial intelligence
digital transition
Economic ESG Impact Assessments
Environment
machine learning
ERC sector(s)
PE Physical Sciences and Engineering
SH Social Sciences and Humanities
Name supervisor
Salvatore Greco
E-mail
salgreco@unict.it
Name of Department/Faculty/School
Department of Economics and Management
Name of the host University
University of Catania (UNICT)
EUNICE partner e-mail of destination Research
eunice@unict.it
Country
Italy
Thesis level
Master
Minimal language knowledge requisite
English B2
Thesis mode
On-site
Start date
Call deadline
Link to the call
Length of the research internship
12 months
Financial support available (other than E+)
Yes