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Bayesian insights on digitalization and environmental sustainability practices: towards the twin transition in the EU
[journal article]
Abstract Utilizing a Bayesian network approach, this paper uncovers the probabilistic relationships between digital technologies (DTs) and environmental sustainability practices (ESs), aiming to identify specific portfolios of digital solutions that significantly contribute to environmentally friendly strate... view more
Utilizing a Bayesian network approach, this paper uncovers the probabilistic relationships between digital technologies (DTs) and environmental sustainability practices (ESs), aiming to identify specific portfolios of digital solutions that significantly contribute to environmentally friendly strategies of European firms. Data are from a sample of 10,583 European firms surveyed in 2020 through Flash Eurobarometer 486. Results reveal that the adoption of a "one instrument, one objective" approach highlights high-speed infrastructure as optimal for recycling and waste reduction, while an approach involving "more instruments, joint scopes" demonstrates the highest probability of circular economy (CE) practices with specific combinations of DTs. Importantly, the paper contributes to illuminating the current representation of twin transition by assessing the effect of DTs by comparing conditional probabilities with marginal probabilities across a multitude of outcomes (optimal DTs and ES combinations), thereby offering implications for research, managerial practice, and policymaking.... view less
Keywords
recycling management; EU; sustainability; firm; digitalization; environmental safety
Classification
Management Science
Free Keywords
Bayesian networks; circular economy; digital technologies; environmental sustainability practices; Industry 4.0; Flash Eurobarometer 486 (SMEs, Start-ups, Scale-ups and Entrepreneurship) (ZA7637 v2.0.0, doi:10.4232/1.13639)
Document language
English
Publication Year
2025
Page/Pages
p. 417-432
Journal
Business Strategy and the Environment, 34 (2025) 1
DOI
https://doi.org/10.1002/bse.3985
ISSN
1099-0836
Status
Published Version; peer reviewed